Explore learning offerings, from self-paced to instructor-led courses, across personas
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注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"34194","entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-mandarin-chinese-6666"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-mandarin-chinese-6666"}}],"nid":34194,"vid":254763,"title":"Building ETL Pipelines with SQL - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程讲授如何在 Databricks Data Intelligence Platform 上使用纯 SQL 构建生产就绪的 ETL 管道。学员将学习以下内容：使用 Auto Loader 的流式处理表（用于增量摄取）、具有增量 刷新 功能的物化视图（用于白银到黄金的转换）、AUTO CDC（FLOW AUTO CDC）（用于声明式 SCD Type 1 和 Type 2 维度管理），以及 Apache Spark Declarative Pipelines（SDP）——将上述对象组合成具有数据质量期望、PRIVATE 表和统一监控功能的生产多表管道。本课程以一个真实的零售数据集为例，贯穿金银铜架构（铜 → 白银 → 黄金）的完整流程。使用 Lakeflow Jobs 进行编排作为附加模块提供。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33999","entityUrl":{"path":"/training/catalog/agentic-application-fundamentals-mandarin-chinese-6667"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/agentic-application-fundamentals-mandarin-chinese-6667"}}],"nid":33999,"vid":254540,"title":"Agentic Application Fundamentals - Mandarin Chinese","price":"0.00","duration":3600,"body":{"processed":"AI 已经改变了开发者被要求构建的内容：智能体、副驾驶及智能工具正从实验阶段迈入生产阶段，工作重心也从编写代码转向协调模型、数据和服务。在本课程中，您将了解在数据所在之处构建智能体应用程序如何消除拼接碎片化技术栈所带来的基础设施开销。通过一个以账户简报为主题的引导式演示，您将看到 Databricks Apps、Lakebase 和 Agent Bricks（Genie Spaces、Knowledge Assistants 和 Supervisor Agents）如何在一个统一的、受治理的 serverless 基础之上协同工作，从而交付一个生产就绪的智能体应用程序。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33988","entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-mandarin-chinese-6599"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-mandarin-chinese-6599"}}],"nid":33988,"vid":254511,"title":"Data Preparation for Machine Learning - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程专注于使用 Databricks 为机器学习准备数据的基础知识。学员将学习探索、清洗和整理数据的核心技能，这些技能专为传统机器学习应用而设计。主要主题包括数据可视化、特征工程以及最优特征存储策略。通过实践练习，学员将获得在 Databricks 中高效准备机器学习数据集的实操经验。本课程面向初级数据科学家、机器学习从业者，以及希望提升数据准备能力的人员，旨在为成功部署机器学习模型奠定坚实基础。
注意：
本课程专注于使用 Databricks 为机器学习准备数据的基础知识。学员将学习探索、清洗和整理数据的核心技能，这些技能专为传统机器学习应用而设计。主要主题包括数据可视化、特征工程以及最优特征存储策略。通过实践练习，学员将获得在 Databricks 中高效准备机器学习数据集的实操经验。本课程面向初级数据科学家、机器学习从业者，以及希望提升数据准备能力的人员，旨在为成功部署机器学习模型奠定坚实基础。
注意：
Databricks Apps 使您能够直接在 Databricks 平台上构建和部署交互式数据与 AI 应用程序。但成功的 AI 辅助开发不仅仅是生成代码——它更关乎建立有效的工作流。
在本实践课程中，您将以 Genie Code 作为 AI 开发助手，从零开始构建一个以 Lakebase 为后端的 Databricks App。在此过程中，您将学习一套实用且可重复的 AI 辅助开发方法：在生成代码之前明确表达意图、以小步骤可验证的方式推进工作、充分利用可复用的 Genie Code Skills，以及将 AI 生成的输出视为需要审查和优化的内容——而非直接接受。
您将创建并部署一个 Databricks App，配置并连接 Lakebase 数据库作为其事务存储，实现 CRUD 运营，并使用 Genie Code 加速常见的开发任务。课程结束时，您不仅将拥有一个可运行的应用程序，还将掌握一套在未来 software 项目中与 AI 高效协作的实用框架。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33995","entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-mandarin-chinese-6659"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-mandarin-chinese-6659"}}],"nid":33995,"vid":254518,"title":"Building Databricks Apps with Genie Code and Lakebase - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"Databricks Apps 使您能够直接在 Databricks 平台上构建和部署交互式数据与 AI 应用程序。但成功的 AI 辅助开发不仅仅是生成代码——它更关乎建立有效的工作流。
在本实践课程中，您将以 Genie Code 作为 AI 开发助手，从零开始构建一个以 Lakebase 为后端的 Databricks App。在此过程中，您将学习一套实用且可重复的 AI 辅助开发方法：在生成代码之前明确表达意图、以小步骤可验证的方式推进工作、充分利用可复用的 Genie Code Skills，以及将 AI 生成的输出视为需要审查和优化的内容——而非直接接受。
您将创建并部署一个 Databricks App，配置并连接 Lakebase 数据库作为其事务存储，实现 CRUD 运营，并使用 Genie Code 加速常见的开发任务。课程结束时，您不仅将拥有一个可运行的应用程序，还将掌握一套在未来 software 项目中与 AI 高效协作的实用框架。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33980","entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-mandarin-chinese-6655"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-mandarin-chinese-6655"}}],"nid":33980,"vid":254412,"title":"Building Reliable Conversational Agents with Genie - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程将教您如何设计、构建和维护 Databricks Genie Agent——一种自然语言界面，使业务用户能够针对受治理的数据提出问题，并获得基于 SQL 的答案，而无需编写代码。
您将了解 Genie Agent 如何融入 Databricks AI/BI 产品系列，以及它们如何将自然语言转换为可靠的 SQL 查询。本课程重点介绍如何创建一个能够提供准确、一致且可信结果的 Genie Agent。
您将遵循完整的端到端工作流，从理解源数据、定义基准，到使用全套 Knowledge Store 管理工具对 Genie Agent 进行配置和优化。这些工具包括元数据、同义词、提示匹配、SQL 逻辑、示例查询和文本说明。
您还将学习如何通过 Genie One 与业务用户共享 Genie Agent，了解 Unity Catalog 治理如何自动执行，并利用监控和用户反馈持续提升质量。
完成本课程后，您将能够创建和管理一个生产就绪的 Genie Agent，以可扩展的方式提供受治理的自助式对话分析。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33981","entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-mandarin-chinese-6656"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-mandarin-chinese-6656"}}],"nid":33981,"vid":254413,"title":"Building Reliable Conversational Agents with Genie - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程将教您如何设计、构建和维护 Databricks Genie Agent——一种自然语言界面，使业务用户能够针对受治理的数据提出问题，并获得基于 SQL 的答案，而无需编写代码。
您将了解 Genie Agent 如何融入 Databricks AI/BI 产品系列，以及它们如何将自然语言转换为可靠的 SQL 查询。本课程重点介绍如何创建一个能够提供准确、一致且可信结果的 Genie Agent。
您将遵循完整的端到端工作流，从理解源数据、定义基准，到使用全套 Knowledge Store 管理工具对 Genie Agent 进行配置和优化。这些工具包括元数据、同义词、提示匹配、SQL 逻辑、示例查询和文本说明。
您还将学习如何通过 Genie One 与业务用户共享 Genie Agent，了解 Unity Catalog 治理如何自动执行，并利用监控和用户反馈持续提升质量。
完成本课程后，您将能够创建和管理一个生产就绪的 Genie Agent，以可扩展的方式提供受治理的自助式对话分析。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33977","entityUrl":{"path":"/training/catalog/answering-business-questions-with-databricks-genie-mandarin-chinese-6648"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/answering-business-questions-with-databricks-genie-mandarin-chinese-6648"}}],"nid":33977,"vid":254409,"title":"Answering Business Questions with Databricks Genie - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程介绍 Databricks Genie One——一个以 AI 为驱动的协作环境，专为满足您的需求和工作而设计。在此环境中，您可以用自然语言就组织数据提出问题，获取受治理的安全答案，调度报告以自动运行，并自动化您的工作流，从而更快、更准确地完成更多工作——因为它以您的数据和业务为基础。您将了解 Genie、Genie One 和 Genie Agents 分别是什么，它们如何保障数据安全，以及获取最佳结果的最佳实践。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33978","entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-mandarin-chinese-6649"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-mandarin-chinese-6649"}}],"nid":33978,"vid":254410,"title":"Building Enterprise Applications with Databricks Apps - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程介绍 Databricks Apps——一项赋能开发者直接在 Databricks 平台上构建和部署安全数据与 AI 应用的新功能。本课程主要面向数据科学家、数据工程师以及需要创建自定义应用的开发者，帮助他们将数据洞察以易于访问的方式呈现给组织内的非技术用户。
课程首先概述 Databricks Apps 的主要组成部分，随后演示如何部署一个与外部服务集成的简单应用。接下来，您将学习如何构建和部署与 Databricks 平台功能集成的智能数据驱动应用。课程还将介绍如何在 Databricks 环境之外开发应用，最后以详细讲解实施安全可靠的企业级应用的最佳实践作为结尾。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33979","entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-mandarin-chinese-6650"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-mandarin-chinese-6650"}}],"nid":33979,"vid":254411,"title":"Building Enterprise Applications with Databricks Apps - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程介绍 Databricks Apps——一项赋能开发者直接在 Databricks 平台上构建和部署安全数据与 AI 应用的新功能。本课程主要面向数据科学家、数据工程师以及需要创建自定义应用的开发者，帮助他们将数据洞察以易于访问的方式呈现给组织内的非技术用户。
课程首先概述 Databricks Apps 的主要组成部分，随后演示如何部署一个与外部服务集成的简单应用。接下来，您将学习如何构建和部署与 Databricks 平台功能集成的智能数据驱动应用。课程还将介绍如何在 Databricks 环境之外开发应用，最后以详细讲解实施安全可靠的企业级应用的最佳实践作为结尾。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33951","entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-5353"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-5353"}}],"nid":33951,"vid":254319,"title":"Building ETL Pipelines with SQL","price":"75.00","duration":10800,"body":{"processed":"This course teaches how to build production-ready ETL pipelines using pure SQL on the Databricks Data Intelligence Platform. Students learn Streaming Tables with Auto Loader for incremental ingestion, Materialized Views with incremental refresh for Silver-to-Gold transformations, AUTO CDC (FLOW AUTO CDC) for declarative SCD Type 1 and Type 2 dimension management, and Apache Spark Declarative Pipelines (SDP) to group these objects into production multi-table pipelines with data quality expectations, PRIVATE tables, and unified monitoring. The course follows a realistic retail dataset through the medallion architecture (Bronze → Silver → Gold). Orchestrating with Lakeflow Jobs is available as a bonus module.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33947","entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-5350"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-etl-pipelines-with-sql-5350"}}],"nid":33947,"vid":254301,"title":"Building ETL Pipelines with SQL","price":"0.00","duration":7200,"body":{"processed":"This course teaches how to build production-ready ETL pipelines using pure SQL on the Databricks Data Intelligence Platform. Students learn Streaming Tables with Auto Loader for incremental ingestion, Materialized Views with incremental refresh for Silver-to-Gold transformations, AUTO CDC (FLOW AUTO CDC) for declarative SCD Type 1 and Type 2 dimension management, and Apache Spark Declarative Pipelines (SDP) to group these objects into production multi-table pipelines with data quality expectations, PRIVATE tables, and unified monitoring. The course follows a realistic retail dataset through the medallion architecture (Bronze → Silver → Gold). Orchestrating with Lakeflow Jobs is available as a bonus module.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33946","entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6623"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6623"}}],"nid":33946,"vid":254299,"title":"Building Databricks Apps with Genie Code and Lakebase","price":"75.00","duration":10800,"body":{"processed":"Databricks Apps make it possible to build and deploy interactive data and AI applications directly on the Databricks platform. But successful AI-assisted development is about more than generating code—it's about developing an effective workflow.
In this course, you'll learn to build a Lakebase-backed Databricks App from the ground up using Genie Code as your AI development assistant. Along the way, you'll learn a practical, repeatable approach to AI-assisted development: clearly specifying intent before generating code, working in small, verifiable increments, leveraging reusable Genie Code Skills, and treating AI-generated output as something to review and refine—not simply accept.
You'll create and deploy a Databricks App, provision and connect a Lakebase database as its transactional store, implement CRUD operations, and use Genie Code to accelerate common development tasks. By the end of the course, you'll not only have a working application, but also a practical framework for collaborating effectively with AI on future software projects.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33941","entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6622"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6622"}}],"nid":33941,"vid":254292,"title":"Building Databricks Apps with Genie Code and Lakebase","price":"0.00","duration":7200,"body":{"processed":"Databricks Apps make it possible to build and deploy interactive data and AI applications directly on the Databricks platform. But successful AI-assisted development is about more than generating code—it's about developing an effective workflow.
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You'll create and deploy a Databricks App, provision and connect a Lakebase database as its transactional store, implement CRUD operations, and use Genie Code to accelerate common development tasks. By the end of the course, you'll not only have a working application, but also a practical framework for collaborating effectively with AI on future software projects.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33894","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-mandarin-chinese-5483"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-mandarin-chinese-5483"}}],"nid":33894,"vid":254029,"title":"Get Started with Databricks for Generative AI - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程提供 Databricks Data Intelligence Platform 的实践入门，重点介绍用于构建和部署生成式 AI 系统的关键组件与功能。学员将了解 Databricks 如何促进可扩展生成式 AI 解决方案的开发，并浏览 AI Search、Agent Framework 以及 MLflow 的生成式 AI 功能（用于模型追踪与日志记录）等工具。本课程包含构建和评估 Retrieval-Augmented Generation (RAG) 管道、部署生成式 AI 智能体，以及利用评估框架优化性能的实践经验。课程结束时，学员将具备在 Databricks Data Intelligence Platform 上设计、部署和监控常见生成式 AI 应用程序的技能。
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33895","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-mandarin-chinese-5484"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-mandarin-chinese-5484"}}],"nid":33895,"vid":254030,"title":"Get Started with Databricks for Generative AI - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程提供 Databricks Data Intelligence Platform 的实践入门，重点介绍用于构建和部署生成式 AI 系统的关键组件与功能。学员将了解 Databricks 如何促进可扩展生成式 AI 解决方案的开发，并浏览 AI Search、Agent Framework 以及 MLflow 的生成式 AI 功能（用于模型追踪与日志记录）等工具。本课程包含构建和评估 Retrieval-Augmented Generation (RAG) 管道、部署生成式 AI 智能体，以及利用评估框架优化性能的实践经验。课程结束时，学员将具备在 Databricks Data Intelligence Platform 上设计、部署和监控常见生成式 AI 应用程序的技能。
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33888","entityUrl":{"path":"/training/catalog/omnigent-basics-6606"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/omnigent-basics-6606"}}],"nid":33888,"vid":253954,"title":"Omnigent Basics","price":"75.00","duration":14400,"body":{"processed":"This course is an introduction to Omnigent, Databricks' open-source meta-harness for AI agents, and how to build, govern, and collaborate on agents with it on the Databricks platform. You'll learn what a harness is and how a meta-harness sits above the agent tools you already use to make them interoperable, and you'll explore Omnigent's three pillars: Combine, Control, and Share. Through interactive lectures and labs, you'll start Omnigent sessions on the Databricks Sandbox, vibe-code and share applications, declare portable YAML agents, enforce stateful contextual policies (including defenses against the lethal trifecta and prompt injection), and work with the built-in Polly and Debby agents. By the end of this course, you'll understand how to coordinate and govern AI agents using Omnigent, Unity Gateway, and the Databricks Sandbox.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33889","entityUrl":{"path":"/training/catalog/omnigent-basics-6608"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/omnigent-basics-6608"}}],"nid":33889,"vid":253955,"title":"Omnigent Basics","price":"0.00","duration":10800,"body":{"processed":"This course is an introduction to Omnigent, Databricks' open-source meta-harness for AI agents, and how to build, govern, and collaborate on agents with it on the Databricks platform. You'll learn what a harness is and how a meta-harness sits above the agent tools you already use to make them interoperable, and you'll explore Omnigent's three pillars: Combine, Control, and Share. Through interactive lectures and labs, you'll start Omnigent sessions on the Databricks Sandbox, vibe-code and share applications, declare portable YAML agents, enforce stateful contextual policies (including defenses against the lethal trifecta and prompt injection), and work with the built-in Polly and Debby agents. By the end of this course, you'll understand how to coordinate and govern AI agents using Omnigent, Unity Gateway, and the Databricks Sandbox.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33866","entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-mandarin-chinese-6540"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-mandarin-chinese-6540"}}],"nid":33866,"vid":253769,"title":"Data Ingestion with Lakeflow Connect - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程全面介绍 LakeFlow Connect——一种可扩展且简便的解决方案，用于将来自各种来源的数据摄取到 Databricks 中。您将首先浏览 LakeFlow Connect 连接器的不同类型（标准型和托管型），并学习各种数据摄取技术，包括批处理摄取、增量批处理摄取和流式处理摄取。您还将了解使用 Delta 表和金银铜架构的主要优势。
接下来，您将培养使用 LakeFlow Connect 标准连接器从云对象存储摄取数据的实践技能。这包括使用 CREATE TABLE AS SELECT（CTAS）、COPY INTO 和 Auto Loader 等方法，并重点介绍每种方法的优势和注意事项。您还将学习如何在将数据摄取到 Databricks Data Intelligence Platform 的过程中，向铜层表追加元数据列。课程随后介绍如何使用救援数据列处理与表架构不匹配的记录，以及管理和分析此类数据的策略。您还将探索摄取和展平半结构化 JSON 数据的技术。
此后，您将探索如何使用 LakeFlow Connect 托管连接器执行企业级数据摄取，以引入来自数据库和软件即服务（SaaS）应用程序的数据。课程还将介绍 Partner Connect，作为将合作伙伴工具集成到摄取工作负载中的一种选项。
最后，课程以替代摄取策略作为总结，包括 MERGE INTO 运营以及利用 Databricks Marketplace，为您奠定坚实的基础，以支持现代数据工程用例。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33867","entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-mandarin-chinese-6541"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-mandarin-chinese-6541"}}],"nid":33867,"vid":253770,"title":"Data Ingestion with Lakeflow Connect - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程全面介绍 LakeFlow Connect——一种可扩展且简便的解决方案，用于将来自各种来源的数据摄取到 Databricks 中。您将首先浏览 LakeFlow Connect 连接器的不同类型（标准型和托管型），并学习各种数据摄取技术，包括批处理摄取、增量批处理摄取和流式处理摄取。您还将了解使用 Delta 表和金银铜架构的主要优势。
接下来，您将培养使用 LakeFlow Connect 标准连接器从云对象存储摄取数据的实践技能。这包括使用 CREATE TABLE AS SELECT（CTAS）、COPY INTO 和 Auto Loader 等方法，并重点介绍每种方法的优势和注意事项。您还将学习如何在将数据摄取到 Databricks Data Intelligence Platform 的过程中，向铜层表追加元数据列。课程随后介绍如何使用救援数据列处理与表架构不匹配的记录，以及管理和分析此类数据的策略。您还将探索摄取和展平半结构化 JSON 数据的技术。
此后，您将探索如何使用 LakeFlow Connect 托管连接器执行企业级数据摄取，以引入来自数据库和软件即服务（SaaS）应用程序的数据。课程还将介绍 Partner Connect，作为将合作伙伴工具集成到摄取工作负载中的一种选项。
最后，课程以替代摄取策略作为总结，包括 MERGE INTO 运营以及利用 Databricks Marketplace，为您奠定坚实的基础，以支持现代数据工程用例。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33864","entityUrl":{"path":"/training/catalog/feature-engineering-at-scale-4706"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/feature-engineering-at-scale-4706"}}],"nid":33864,"vid":253765,"title":"Feature Engineering at Scale","price":"0.00","duration":10800,"body":{"processed":"In this course, you will gain a comprehensive understanding of how to design, scale, and operationalize end-to-end feature engineering pipelines on the Databricks platform. The curriculum is structured across three progressive modules: mastering the fundamentals of Spark’s distributed execution and optimization, implementing scalable data ingestion with Auto Loader and declarative Lakeflow pipelines, and advancing to production-grade MLOps with the Databricks Feature Store.
You will engage in hands-on learning experiences such as debugging Spark performance with the Catalyst Optimizer and Spark UI, building robust Bronze-Silver-Gold medallion architectures with automated quality checks, and implementing scalable feature transformations using SparkML. The course culminates in deploying real-time feature serving through Online Feature Stores, defining FeatureSpecs with on-demand transformations, and applying governance and lineage tracking with Unity Catalog.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33865","entityUrl":{"path":"/training/catalog/feature-engineering-at-scale-4707"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/feature-engineering-at-scale-4707"}}],"nid":33865,"vid":253766,"title":"Feature Engineering at Scale","price":"75.00","duration":10800,"body":{"processed":"In this course, you will gain a comprehensive understanding of how to design, scale, and operationalize end-to-end feature engineering pipelines on the Databricks platform. The curriculum is structured across three progressive modules: mastering the fundamentals of Spark’s distributed execution and optimization, implementing scalable data ingestion with Auto Loader and declarative Lakeflow pipelines, and advancing to production-grade MLOps with the Databricks Feature Store.
You will engage in hands-on learning experiences such as debugging Spark performance with the Catalyst Optimizer and Spark UI, building robust Bronze-Silver-Gold medallion architectures with automated quality checks, and implementing scalable feature transformations using SparkML. The course culminates in deploying real-time feature serving through Online Feature Stores, defining FeatureSpecs with on-demand transformations, and applying governance and lineage tracking with Unity Catalog.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33863","entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-mandarin-chinese-6567"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-mandarin-chinese-6567"}}],"nid":33863,"vid":253742,"title":"DevOps Essentials for Data Engineering - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程探讨软件工程最佳实践与 DevOps 原则，专为使用 Databricks 的数据工程师量身设计。学员将在代码质量、版本控制、文档编写和测试等关键主题上打下坚实基础。课程重点介绍 DevOps，涵盖其核心组件、优势，以及持续集成与持续交付（CI/CD）在优化数据工程工作流中所发挥的作用。
您将学习如何在 PySpark 中应用模块化原则，以创建可复用组件并高效组织代码结构。实践环节包括：使用 pytest 框架为 PySpark 函数设计并实现单元测试，以及使用 Spark Declarative Pipeline 和 Jobs 对 Databricks 数据管道进行集成测试，以确保其可靠性。
课程还涵盖 Databricks 中的基本 Git 运营操作，包括使用 Databricks Git Folders 集成持续集成实践。最后，您将从宏观层面了解 Databricks 资产的多种部署方式，例如 REST API、CLI、SDK 以及 Declarative Automation Bundles（DABs），从而掌握部署和管理管道的相关技术知识。
完成本课程后，您将熟练掌握软件工程与 DevOps 最佳实践，从而能够构建可扩展、易维护且高效的数据工程解决方案。
注意：
1. 这是“Data Engineering with Databricks”系列课程中的第四门课程。
2. 对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33862","entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-mandarin-chinese-6566"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-mandarin-chinese-6566"}}],"nid":33862,"vid":253741,"title":"DevOps Essentials for Data Engineering - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程探讨软件工程最佳实践与 DevOps 原则，专为使用 Databricks 的数据工程师量身设计。学员将在代码质量、版本控制、文档编写和测试等关键主题上打下坚实基础。课程重点介绍 DevOps，涵盖其核心组件、优势，以及持续集成与持续交付（CI/CD）在优化数据工程工作流中所发挥的作用。
您将学习如何在 PySpark 中应用模块化原则，以创建可复用组件并高效组织代码结构。实践环节包括：使用 pytest 框架为 PySpark 函数设计并实现单元测试，以及使用 Spark Declarative Pipeline 和 Jobs 对 Databricks 数据管道进行集成测试，以确保其可靠性。
课程还涵盖 Databricks 中的基本 Git 运营操作，包括使用 Databricks Git Folders 集成持续集成实践。最后，您将从宏观层面了解 Databricks 资产的多种部署方式，例如 REST API、CLI、SDK 以及 Declarative Automation Bundles（DABs），从而掌握部署和管理管道的相关技术知识。
完成本课程后，您将熟练掌握软件工程与 DevOps 最佳实践，从而能够构建可扩展、易维护且高效的数据工程解决方案。
注意：
1. 这是“Data Engineering with Databricks”系列课程中的第四门课程。
2. 对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33858","entityUrl":{"path":"/training/catalog/deploy-workloads-with-lakeflow-jobs-mandarin-chinese-6543"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/deploy-workloads-with-lakeflow-jobs-mandarin-chinese-6543"}}],"nid":33858,"vid":253736,"title":"Deploy Workloads with Lakeflow Jobs - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"
《使用 Lakeflow Jobs 部署工作负载》课程讲授如何在 Databricks 生态系统中，以 Lakeflow Jobs 作为统一编排平台，对数据、分析及 AI 工作流进行编排与自动化。
• 您将学习如何使用有向 Acyclic 图（DAG）设计并实现数据工作负载、配置各种调度选项，以及实现高级工作流功能，例如条件任务执行、run-if 依赖关系和 for each 循环。
• 本课程涵盖创建健壮、可投入生产的流水线的最佳实践，包括合理的 compute 选择、模块化编排、错误处理技术以及容错设计——所有这些均原生集成于 Databricks Data Intelligence Platform 之中。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33859","entityUrl":{"path":"/training/catalog/deploy-workloads-with-lakeflow-jobs-mandarin-chinese-6544"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/deploy-workloads-with-lakeflow-jobs-mandarin-chinese-6544"}}],"nid":33859,"vid":253737,"title":"Deploy Workloads with Lakeflow Jobs - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"《使用 Lakeflow Jobs 部署工作负载》课程讲授如何在 Databricks 生态系统中，以 Lakeflow Jobs 作为统一编排平台，对数据、分析及 AI 工作流进行编排与自动化。
• 您将学习如何使用有向 Acyclic 图（DAG）设计并实现数据工作负载、配置各种调度选项，以及实现高级工作流功能，例如条件任务执行、run-if 依赖关系和 for each 循环。
• 本课程涵盖创建健壮、可投入生产的流水线的最佳实践，包括合理的 compute 选择、模块化编排、错误处理技术以及容错设计——所有这些均原生集成于 Databricks Data Intelligence Platform 之中。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33860","entityUrl":{"path":"/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-mandarin-chinese-6569"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-mandarin-chinese-6569"}}],"nid":33860,"vid":253738,"title":"Build Data Pipelines with Lakeflow Spark Declarative Pipelines - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程向用户介绍使用 Databricks 中的 Apache Spark™ Declarative Pipelines (SDP) 构建数据管道所需的基本概念和技能，涵盖通过多个流式处理表和物化视图进行增量批处理或流式处理摄取与处理。本课程专为初次接触 Spark Declarative Pipelines 的数据工程师设计，全面介绍核心组件，包括增量数据处理、流式处理表、物化视图和临时视图，并重点说明其各自的用途与区别。
课程涵盖以下主题：
• 使用 Spark Declarative Pipelines 中的多文件编辑器，通过 SQL 开发和调试 ETL 管道（并提供 Python 代码示例）
• Spark Declarative Pipelines 如何通过管道图形跟踪管道中的数据依赖关系
• 配置管道 compute 资源、数据资产、触发器模式及其他高级选项
随后，课程介绍 Spark Declarative Pipelines 中的数据质量期望，引导用户将期望集成到管道中，以验证和强制执行数据完整性。学员还将浏览如何将管道投入生产，包括调度选项，以及启用管道事件日志记录以监控管道性能和健康状况。
最后，课程介绍如何在 Spark Declarative Pipelines 中使用 AUTO CDC INTO 语法实现变更数据捕获 (CDC)，以管理缓慢变化维度（SCD Type 1 和 Type 2），帮助用户将 CDC 集成到自己的管道中。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击‘Next Lesson’按钮，否则可能会导致 SCORM 模块无法标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33861","entityUrl":{"path":"/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-mandarin-chinese-6570"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-mandarin-chinese-6570"}}],"nid":33861,"vid":253739,"title":"Build Data Pipelines with Lakeflow Spark Declarative Pipelines - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程向用户介绍使用 Databricks 中的 Apache Spark™ Declarative Pipelines (SDP) 构建数据管道所需的基本概念和技能，涵盖通过多个流式处理表和物化视图进行增量批处理或流式处理摄取与处理。本课程专为初次接触 Spark Declarative Pipelines 的数据工程师设计，全面介绍核心组件，包括增量数据处理、流式处理表、物化视图和临时视图，并重点说明其各自的用途与区别。
课程涵盖以下主题：
• 使用 Spark Declarative Pipelines 中的多文件编辑器，通过 SQL 开发和调试 ETL 管道（并提供 Python 代码示例）
• Spark Declarative Pipelines 如何通过管道图形跟踪管道中的数据依赖关系
• 配置管道 compute 资源、数据资产、触发器模式及其他高级选项
随后，课程介绍 Spark Declarative Pipelines 中的数据质量期望，引导用户将期望集成到管道中，以验证和强制执行数据完整性。学员还将浏览如何将管道投入生产，包括调度选项，以及启用管道事件日志记录以监控管道性能和健康状况。
最后，课程介绍如何在 Spark Declarative Pipelines 中使用 AUTO CDC INTO 语法实现变更数据捕获 (CDC)，以管理缓慢变化维度（SCD Type 1 和 Type 2），帮助用户将 CDC 集成到自己的管道中。
注意：对于 SCORM 课程文件，请确保完成内容后关闭 SCORM 窗口。请勿点击‘Next Lesson’按钮，否则可能会导致 SCORM 模块无法标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33853","entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6590"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-6590"}}],"nid":33853,"vid":253716,"title":"Building Databricks Apps with Genie Code and Lakebase","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps make it possible to build and deploy interactive data and AI applications directly on the Databricks platform. But successful AI-assisted development is about more than generating code—it's about developing an effective workflow.
In this course, you'll learn to build a Lakebase-backed Databricks App from the ground up using Genie Code as your AI development assistant. Along the way, you'll learn a practical, repeatable approach to AI-assisted development: clearly specifying intent before generating code, working in small, verifiable increments, leveraging reusable Genie Code Skills, and treating AI-generated output as something to review and refine—not simply accept.
You'll create and deploy a Databricks App, provision and connect a Lakebase database as its transactional store, implement CRUD operations, and use Genie Code to accelerate common development tasks. By the end of the course, you'll not only have a working application, but also a practical framework for collaborating effectively with AI on future software projects.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-08T13:00:00"},"endDate":{"value":"2026-10-08T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"America/Los_Angeles"}},{"entity":{"startDate":{"value":"2026-11-25T13:00:00"},"endDate":{"value":"2026-11-25T17:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2026-12-16T13:00:00"},"endDate":{"value":"2026-12-16T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T13:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2027-01-27T13:00:00"},"endDate":{"value":"2027-01-27T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-27T13:00:00"},"endDate":{"value":"2027-01-27T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-27T13:00:00"},"endDate":{"value":"2027-01-27T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-27T13:00:00"},"endDate":{"value":"2027-01-27T17:00:00"},"timezone":"America/New_York"}}]},{"id":"33836","entityUrl":{"path":"/training/catalog/stream-processing-and-analysis-with-apache-spark-3944"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/stream-processing-and-analysis-with-apache-spark-3944"}}],"nid":33836,"vid":253587,"title":"Stream Processing and Analysis with Apache Spark™","price":"75.00","duration":10800,"body":{"processed":"This course guides learners on how to develop scalable, fault-tolerant stream processing applications using the Spark Structured Streaming API on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"33837","entityUrl":{"path":"/training/catalog/stream-processing-and-analysis-with-apache-spark-3959"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/stream-processing-and-analysis-with-apache-spark-3959"}}],"nid":33837,"vid":253588,"title":"Stream Processing and Analysis with Apache Spark™","price":"0.00","duration":7200,"body":{"processed":"This course guides learners on how to develop scalable, fault-tolerant stream processing applications using the Spark Structured Streaming API on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"33830","entityUrl":{"path":"/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-3990"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-3990"}}],"nid":33830,"vid":253549,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks","price":"75.00","duration":10800,"body":{"processed":"This course covers core Databricks platform components and Apache Spark with Delta Lake, focusing on the Lakehouse architecture, Unity Catalog, and data management techniques like ACID transactions and table maintenance. Additionally, it teaches students how to optimize query performance through partitioning, shuffles, and tuning tools, while utilizing the Spark UI to monitor applications and resolve bottlenecks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"33831","entityUrl":{"path":"/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-3993"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-3993"}}],"nid":33831,"vid":253550,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks","price":"0.00","duration":7200,"body":{"processed":"This course covers core Databricks platform components and Apache Spark with Delta Lake, focusing on the Lakehouse architecture, Unity Catalog, and data management techniques like ACID transactions and table maintenance. Additionally, it teaches students how to optimize query performance through partitioning, shuffles, and tuning tools, while utilizing the Spark UI to monitor applications and resolve bottlenecks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"33334","entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-mandarin-chinese-6507"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-mandarin-chinese-6507"}}],"nid":33334,"vid":252741,"title":"Get Started with Databricks: End to End - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程是对 Databricks Data Intelligence Platform 的全面实践入门课程。您将跟随一段完整的端到端学习旅程，从工作区出发，最终完成对 AI 与机器学习的入门介绍，涵盖在 Databricks 上处理数据所需的日常技能。
课程内容包括：
完成本课程后，您将能够熟练导航 Databricks、在 Unity Catalog 中查找和管理数据、在 AI 辅助下编写 SQL 和笔记本代码、构建仪表盘，以及使用 Genie 探索数据。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则 SCORM 模块可能无法标记为已完成。
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
本课程是对 Databricks Data Intelligence Platform 的全面实践入门课程。您将跟随一段完整的端到端学习旅程，从工作区出发，最终完成对 AI 与机器学习的入门介绍，涵盖在 Databricks 上处理数据所需的日常技能。
课程内容包括：
完成本课程后，您将能够熟练导航 Databricks、在 Unity Catalog 中查找和管理数据、在 AI 辅助下编写 SQL 和笔记本代码、构建仪表盘，以及使用 Genie 探索数据。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则 SCORM 模块可能无法标记为已完成。
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33326","entityUrl":{"path":"/training/catalog/external-apps-with-lakebase-sdks-and-production-patterns-6527"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/external-apps-with-lakebase-sdks-and-production-patterns-6527"}}],"nid":33326,"vid":252702,"title":"External Apps with Lakebase: SDKs and Production Patterns","price":"75.00","duration":3600,"body":{"processed":"Connects apps running outside Databricks to Lakebase. Following the lecture-demo pattern, learners authenticate an external app with a service principal, compare the SDK-native, manual-HTTP, and Data API access paths, and build a production connection manager with pooling, token refresh, and retry on scale-to-zero wake-up.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"33327","entityUrl":{"path":"/training/catalog/advanced-machine-learning-operations-3482"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/advanced-machine-learning-operations-3482"}}],"nid":33327,"vid":252703,"title":"Advanced Machine Learning Operations","price":"75.00","duration":10800,"body":{"processed":"In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Declarative Automation Bundles (DABs), Lakeflow Jobs, and Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.
Note:
1. This course is the second in the series of Advanced Machine Learning.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33328","entityUrl":{"path":"/training/catalog/advanced-machine-learning-operations-3508"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/advanced-machine-learning-operations-3508"}}],"nid":33328,"vid":252704,"title":"Advanced Machine Learning Operations","price":"0.00","duration":7200,"body":{"processed":"In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Declarative Automation Bundles (DABs), Lakeflow Jobs, and Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.
Note:
1. This course is the second in the series of Advanced Machine Learning.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"32123","entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6270"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6270"}}],"nid":32123,"vid":251235,"title":"Get Started with Databricks: End to End","price":"0.00","duration":7200,"body":{"processed":"This course is a comprehensive, hands-on introduction to the Databricks Data Intelligence Platform. You will follow a single end-to-end journey that starts in the workspace and finishes with an introduction to AI and machine learning, covering the everyday skills you need to work with data on Databricks.
The course covers:
• Navigating the Databricks workspace, compute options, and the Lakehouse versus Genie experiences.
• Understanding and ingesting data with Unity Catalog, including file upload and the Catalog Explorer.
• Working in Databricks notebooks and using Genie Code to write and debug code.
• Querying data with SQL, managing saved queries, and building dashboards and visualizations.
• Exploring data in natural language with Genie Agents.
• An introduction to AI and machine learning with MLflow and the Data Science Agent.
By the end of the course, you will be comfortable navigating Databricks, finding and governing data in Unity Catalog, writing SQL and notebook code with AI assistance, building dashboards, and exploring data with Genie.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32122","entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6269"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6269"}}],"nid":32122,"vid":251234,"title":"Get Started with Databricks: End to End","price":"75.00","duration":10800,"body":{"processed":"This course is a comprehensive, hands-on introduction to the Databricks Data Intelligence Platform. You will follow a single end-to-end journey that starts in the workspace and finishes with an introduction to AI and machine learning, covering the everyday skills you need to work with data on Databricks.
The course covers:
• Navigating the Databricks workspace, compute options, and the Lakehouse versus Genie experiences.
• Understanding and ingesting data with Unity Catalog, including file upload and the Catalog Explorer.
• Working in Databricks notebooks and using Genie Code to write and debug code.
• Querying data with SQL, managing saved queries, and building dashboards and visualizations.
• Exploring data in natural language with Genie Agents.
• An introduction to AI and machine learning with MLflow and the Data Science Agent.
By the end of the course, you will be comfortable navigating Databricks, finding and governing data in Unity Catalog, writing SQL and notebook code with AI assistance, building dashboards, and exploring data with Genie.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32120","entityUrl":{"path":"/training/catalog/developing-applications-with-apache-spark-3957"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/developing-applications-with-apache-spark-3957"}}],"nid":32120,"vid":251205,"title":"Developing Applications with Apache Spark™","price":"75.00","duration":10800,"body":{"processed":"Master scalable data processing with Apache Spark in this course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"32121","entityUrl":{"path":"/training/catalog/developing-applications-with-apache-spark-3962"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/developing-applications-with-apache-spark-3962"}}],"nid":32121,"vid":251206,"title":"Developing Applications with Apache Spark™","price":"0.00","duration":7200,"body":{"processed":"Master scalable data processing with Apache Spark in this course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"32115","entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-accreditation-mandarin-chinese-6484"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-accreditation-mandarin-chinese-6484"}}],"nid":32115,"vid":251042,"title":"AI Agent Fundamentals Accreditation - Mandarin Chinese","price":"0.00","duration":1800,"body":{"processed":"欢迎参加 AI 智能体基础认证测验。本测验共包含 20 道题目，旨在测试您对 AI 智能体基础知识、企业应用，以及如何使用 Databricks 的 Mosaic AI 和 Agent Bricks 构建与部署 AI 智能体的了解。成功完成本测验后，您将在 48 小时内通过我们的徽章服务商 Accredible 获得徽章。祝您好运！
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32116","entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-accreditation-4503"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-accreditation-4503"}}],"nid":32116,"vid":251043,"title":"AI Agent Fundamentals Accreditation","price":"0.00","duration":1800,"body":{"processed":"Welcome to the AI Agent Fundamentals Accreditation quiz. In this 20-question quiz, we'll test your knowledge about the fundamentals of AI agent, its enterprise applications, and how to build and deploy them using Databricks' Mosaic AI and Agent Bricks. Upon completing this quiz successfully, you'll be awarded a badge (within 48 hours) via our badging vendor, Accredible. Good luck!
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32086","entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-mandarin-chinese-6487"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-mandarin-chinese-6487"}}],"nid":32086,"vid":250757,"title":"Get Started with Databricks Apps - Mandarin Chinese","price":"0.00","duration":3600,"body":{"processed":"本课程介绍 Databricks Apps，这是一项功能，使开发人员能够直接在 Databricks 平台上构建和部署安全的数据与 AI 应用程序。本课程主要面向数据科学家、数据工程师以及需要创建自定义应用程序的开发人员，帮助他们将数据洞察以易于理解的方式呈现给组织内的非技术用户。
本课程首先概述 Databricks Apps 的主要组件，随后介绍如何部署简单的应用程序，这些应用程序可与外部服务以及 Databricks 资源进行集成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32088","entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-mandarin-chinese-6492"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-mandarin-chinese-6492"}}],"nid":32088,"vid":250759,"title":"Get Started with Databricks Apps - Mandarin Chinese","price":"75.00","duration":7200,"body":{"processed":"本课程介绍 Databricks Apps，这是一项功能，使开发人员能够直接在 Databricks 平台上构建和部署安全的数据与 AI 应用程序。本课程主要面向数据科学家、数据工程师以及需要创建自定义应用程序的开发人员，帮助他们将数据洞察以易于理解的方式呈现给组织内的非技术用户。
本课程首先概述 Databricks Apps 的主要组件，随后介绍如何部署简单的应用程序，这些应用程序可与外部服务以及 Databricks 资源进行集成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32089","entityUrl":{"path":"/training/catalog/introduction-to-apache-spark-3898"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/introduction-to-apache-spark-3898"}}],"nid":32089,"vid":250760,"title":"Introduction to Apache Spark™","price":"75.00","duration":10800,"body":{"processed":"This beginner-friendly course covers the fundamentals of Apache Spark for large-scale data processing. You will explore Spark’s distributed architecture, master the DataFrame API, and learn to read, write, and process data using Python. Through hands-on exercises, you will build the skills needed to execute Spark transformations and actions efficiently.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"32090","entityUrl":{"path":"/training/catalog/introduction-to-apache-spark-3901"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/introduction-to-apache-spark-3901"}}],"nid":32090,"vid":250761,"title":"Introduction to Apache Spark™","price":"0.00","duration":7200,"body":{"processed":"This beginner-friendly course covers the fundamentals of Apache Spark for large-scale data processing. You will explore Spark’s distributed architecture, master the DataFrame API, and learn to read, write, and process data using Python. Through hands-on exercises, you will build the skills needed to execute Spark transformations and actions efficiently.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"32073","entityUrl":{"path":"/training/catalog/databricks-fundamentals-mandarin-chinese-5940"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-fundamentals-mandarin-chinese-5940"}}],"nid":32073,"vid":250689,"title":"Databricks Fundamentals - Mandarin Chinese","price":"0.00","duration":3600,"body":{"processed":"本课程是对 Databricks 和 Databricks Platform 的基础入门介绍。课程将向您介绍现代数据与 AI 团队所面临的挑战、平台核心的湖仓理念、平台所提供的产品与功能、如何通过统一治理确保数据与 AI 的可信度，以及工作区本身的导览。
这些视频按建议顺序排列，但您可以按照自己喜欢的任意顺序观看。此外，我们建议您在尝试参加 Databricks Fundamentals 认证评估之前，先观看所有可用的视频内容。
我们不假设您具备任何关于 Databricks 或数据平台的技术背景知识。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32074","entityUrl":{"path":"/training/catalog/databricks-fundamentals-accreditation-mandarin-chinese-5941"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-fundamentals-accreditation-mandarin-chinese-5941"}}],"nid":32074,"vid":250690,"title":"Databricks Fundamentals Accreditation - Mandarin Chinese","price":"0.00","duration":1800,"body":{"processed":"欢迎参加 Databricks Fundamentals 认证考核。本测验共包含 10 道题，将检验您对 Databricks Data Intelligence Platform 的了解。成功完成测验后，您将在 48 小时内通过我们的徽章服务提供商 Accredible 获得一枚徽章。祝您好运！
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"32062","entityUrl":{"path":"/training/catalog/databricks-fundamentals-2206"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-fundamentals-2206"}}],"nid":32062,"vid":250412,"title":"Databricks Fundamentals","price":"0.00","duration":3600,"body":{"processed":"This course is a fundamental introduction to Databricks and the Databricks Platform. You will be introduced to the problems modern data and AI teams face, the lakehouse idea at the center of the platform, the products and capabilities the platform offers, how it keeps data and AI trustworthy through unified governance, and a guided tour of the workspace itself.
These videos are provided in a suggested order, but you are welcome to watch them in any order you prefer. Additionally, we recommend you watch all the video content available prior to attempting the accreditation assessment for Databricks Fundamentals.
We assume no prior technical knowledge of Databricks or data platforms.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32063","entityUrl":{"path":"/training/catalog/databricks-fundamentals-accreditation-2308"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-fundamentals-accreditation-2308"}}],"nid":32063,"vid":250413,"title":"Databricks Fundamentals Accreditation","price":"0.00","duration":1800,"body":{"processed":"Welcome to the Databricks Fundamentals Accreditation. In this 10-question quiz, we'll test your knowledge about the Databricks Data Intelligence Platform. Upon completing this quiz successfully, you'll be awarded a badge (within 48 hours) via our badging vendor, Accredible. Good luck!
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"32057","entityUrl":{"path":"/training/catalog/answering-business-questions-with-databricks-genie-5777"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/answering-business-questions-with-databricks-genie-5777"}}],"nid":32057,"vid":250363,"title":"Answering Business Questions with Databricks Genie","price":"0.00","duration":7200,"body":{"processed":"This course introduces Databricks Genie One, an AI-powered cowork environment designed around your needs and work, where you can ask questions in plain language about your organization's data and get governed, secure answers, schedule reports to run automatically, and automate your workflow to get more work done faster and more accurately, as it's based on your data and business. You'll learn what Genie, Genie One, and Genie Agents are, how they all keep your data secure, and the best practices for getting the best results.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32054","entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-mandarin-chinese-6483"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-mandarin-chinese-6483"}}],"nid":32054,"vid":250348,"title":"AI Agent Fundamentals - Mandarin Chinese","price":"0.00","duration":5400,"body":{"processed":"本基础课程介绍 AI agents，以及它们在 Databricks 企业应用中的使用，包括 Mosaic AI 平台和 Agent Bricks。学习者将了解什么是 AI agents、它们如何运作，以及它们如何模拟人类推理来处理复杂任务。
课程涵盖真实的 agent 应用场景，并简要介绍 agentic workflows、multi-agent systems 等进阶主题。同时说明 Agent Bricks 如何简化各类应用中企业级 agents 的开发，并通过演示展示如何在 Databricks 上构建和使用 agents。
.
注意：对于 SCORM 课件文件，请在完成内容后关闭 SCORM 窗口。请勿点击 “Next Lesson” 按钮，否则 SCORM 模块可能无法被标记为已完成。
Languages Available: English | 日本語 | Português BR | 한국어
生成式 AI 已从新兴实验演变为企业的核心能力，驱动着从智能客户支持到自动化复杂工作流的 AI 智能体等各类应用。
能够有效部署生成式 AI 的组织——以自身数据为基础、以可信治理为保障——将在各自行业中引领发展步伐。然而，随着新模型每周不断发布、能力持续快速演进，如何战略性地评估和应用生成式 AI，远比追逐最新版本更为重要。通过这门免费的按需训练课程，快速掌握生成式 AI 的核心基础——了解它的能力边界、真正创造商业价值的场景，以及如何在 Databricks 上安全落地实施。
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31916","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-mandarin-chinese-5809"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-mandarin-chinese-5809"}}],"nid":31916,"vid":249983,"title":"Get Started with Databricks for Data Warehousing - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程全面介绍了 Databricks 现代数据仓库方法的实践概览，重点展示数据湖仓架构如何将传统数据仓库的优势与云的灵活性和可扩展性相结合。您将以一家虚构零售商（Vintage Audio Co.）为背景，进行端到端的实践操作——浏览工作区、查询受治理的 Unity Catalog 表、保持 Unity Catalog 托管表的分析读取性能、使用 Auto Loader 增量加载数据、构建星型模式，并通过 Unity Catalog 指标视图提供一致的洞察——所有操作均在单一受治理的环境中完成，并全程内置 AI 驱动功能（Predictive Optimization、Genie Code）。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31917","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-mandarin-chinese-5810"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-mandarin-chinese-5810"}}],"nid":31917,"vid":249984,"title":"Get Started with Databricks for Data Warehousing - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程全面介绍了 Databricks 现代数据仓库方法的实践概览，重点展示数据湖仓架构如何将传统数据仓库的优势与云的灵活性和可扩展性相结合。您将以一家虚构零售商（Vintage Audio Co.）为背景，进行端到端的实践操作——浏览工作区、查询受治理的 Unity Catalog 表、保持 Unity Catalog 托管表的分析读取性能、使用 Auto Loader 增量加载数据、构建星型模式，并通过 Unity Catalog 指标视图提供一致的洞察——所有操作均在单一受治理的环境中完成，并全程内置 AI 驱动功能（Predictive Optimization、Genie Code）。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31918","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-3604"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-warehousing-3604"}}],"nid":31918,"vid":249985,"title":"Get Started with Databricks for Data Warehousing","price":"75.00","duration":10800,"body":{"processed":"This course provides a comprehensive, hands-on overview of Databricks' modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. Working end-to-end with a fictional retailer (Vintage Audio Co.), you will explore the workspace, query governed Unity Catalog tables, keep Unity Catalog managed tables fast for analytical reads, load data incrementally with Auto Loader, model a star schema, and deliver consistent insights through Unity Catalog metric views — all from a single, governed environment, with AI-driven features (Predictive Optimization, Genie Code) built in throughout.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31895","entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-4482"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/ai-agent-fundamentals-4482"}}],"nid":31895,"vid":249807,"title":"AI Agent Fundamentals","price":"0.00","duration":5400,"body":{"processed":"This foundational course introduces AI agents and their use in enterprise applications on Databricks, including the Mosaic AI platform and Agent Bricks. Learners will examine what AI agents are, how they function, and how they mimic human reasoning to handle complex tasks.
The course covers real-world agent use cases and provides a basic introduction to advanced topics such as agentic workflows and multi-agent systems. It also explores how Agent Bricks simplifies the development of enterprise-ready agents across various applications, with demos showing how to build and use agents on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
This is a 20-minute assessment that will test your knowledge of fundamental concepts related to Generative AI.
After successfully completing this assessment, you will be awarded the Databricks Generative AI Fundamentals badge.
• This accreditation is part of Databricks Generative AI Fundamentals Learning Plan.
• Upon an 80% pass rate, you will receive a badge from Databricks.
Languages Available: English | 日本語 | Português BR
Generative AI has moved from emerging experiment to essential enterprise capability, powering everything from intelligent customer support to AI agents that automate complex workflows.
Organizations that understand how to deploy it effectively—grounded in their own data and governed for trust—will be the ones setting the pace in their industries. But with new models releasing weekly and capabilities evolving fast, knowing how to evaluate and apply GenAI strategically matters more than chasing the latest release. Get up to speed on the fundamentals of Generative AI—what it can do, where it delivers real business value, and how to implement it securely on Databricks—with this free on-demand training.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31862","entityUrl":{"path":"/training/catalog/first-steps-with-lakebase-autoscaling-6399"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/first-steps-with-lakebase-autoscaling-6399"}}],"nid":31862,"vid":249271,"title":"First Steps with Lakebase Autoscaling","price":"75.00","duration":3600,"body":{"processed":"The hands-on on-ramp to Lakebase. Learners create their first project (UI and SDK), generate credentials, connect with psycopg, tour the four connection surfaces, and run a full CRUD sequence. It is the practical foundation every later hands-on course assumes.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"31825","entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-mandarin-chinese-6384"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-mandarin-chinese-6384"}}],"nid":31825,"vid":248886,"title":"Get Started with SQL Analytics and BI on Databricks - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程介绍 Databricks Data Intelligence Platform 以及数据分析师在日常 SQL 分析和 BI 工作中所需的核心技能。您将学习如何导航工作区和 Unity Catalog、通过 Serverless SQL Warehouse 针对 Unity Catalog 托管表编写 SQL 查询、使用 Genie 代码生成和调试 SQL、使用 Delta Lake（DML、版本历史、时间旅行和还原）、构建并发布 AI/BI Dashboards，以及创建用于对话式分析的 Genie 智能体。每个主题均配有一个引导式演示笔记本和一个实践实验室。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31826","entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-mandarin-chinese-6385"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-mandarin-chinese-6385"}}],"nid":31826,"vid":248887,"title":"Get Started with SQL Analytics and BI on Databricks - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程介绍 Databricks Data Intelligence Platform 以及数据分析师在日常 SQL 分析和 BI 工作中所需的核心技能。您将学习如何导航工作区和 Unity Catalog、通过 Serverless SQL Warehouse 针对 Unity Catalog 托管表编写 SQL 查询、使用 Genie 代码生成和调试 SQL、使用 Delta Lake（DML、版本历史、时间旅行和还原）、构建并发布 AI/BI Dashboards，以及创建用于对话式分析的 Genie 智能体。每个主题均配有一个引导式演示笔记本和一个实践实验室。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31815","entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-6225"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-6225"}}],"nid":31815,"vid":248696,"title":"Get Started with Databricks Apps","price":"75.00","duration":7200,"body":{"processed":"This course introduces Databricks Apps, a feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.
The course begins provides an overview of the main components of Databricks Apps, followed by the deployment of simple apps that integrates with an external service as well as a Databricks resource.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"31816","entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-6226"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-apps-6226"}}],"nid":31816,"vid":248697,"title":"Get Started with Databricks Apps","price":"0.00","duration":3600,"body":{"processed":"This course introduces Databricks Apps, a feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.
The course begins provides an overview of the main components of Databricks Apps, followed by the deployment of simple apps that integrates with an external service as well as a Databricks resource.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31784","entityUrl":{"path":"/training/catalog/migrating-postgres-workloads-to-lakebase-6357"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/migrating-postgres-workloads-to-lakebase-6357"}}],"nid":31784,"vid":248450,"title":"Migrating Postgres Workloads to Lakebase","price":"75.00","duration":3600,"body":{"processed":"Migrates an existing Postgres workload to Lakebase. Learners use a decision matrix to confirm fit, assemble a pre-migration checklist, execute a pg_dump/pg_restore migration (and its alternatives), and design a cutover strategy with validation queries that catch subtle drift.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31782","entityUrl":{"path":"/training/catalog/lakebase-production-operations-6353"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/lakebase-production-operations-6353"}}],"nid":31782,"vid":248430,"title":"Lakebase Production Operations","price":"75.00","duration":3600,"body":{"processed":"Hardens Lakebase for production. Following the lecture-demo pattern and framed around an incident, learners configure High Availability across zones, add read replicas and route analytical traffic to them, tune the restore window, and recover from data loss with a point-in-time branch.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31779","entityUrl":{"path":"/training/catalog/vector-search-and-rag-with-pgvector-on-lakebase-6351"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/vector-search-and-rag-with-pgvector-on-lakebase-6351"}}],"nid":31779,"vid":248424,"title":"Vector Search and RAG with pgvector on Lakebase","price":"75.00","duration":3600,"body":{"processed":"Builds a semantic retrieval layer on pgvector inside Lakebase Postgres, taught against a live \"Ask the docs\" app that Classroom Setup deploys. Following the lecture-demo pattern, learners decide when pgvector beats Databricks AI Search, design a document/chunk schema, choose and build HNSW and IVFFlat indexes, generate embeddings in batch with ai_query(), and write a hybrid search combining vector similarity, a metadata filter, and full-text ranking (ts_rank_cd cover-density) in one query. An optional closing section surveys Lakebase Search (Beta) and its lakebase_text (BM25) and lakebase_vector (ANN) extensions.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31777","entityUrl":{"path":"/training/catalog/ai-agents-and-long-term-memory-on-lakebase-6349"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/ai-agents-and-long-term-memory-on-lakebase-6349"}}],"nid":31777,"vid":248413,"title":"AI Agents and Long-Term Memory on Lakebase","price":"75.00","duration":3600,"body":{"processed":"Gives AI agents durable memory on Lakebase. Following the lecture-demo pattern, learners distinguish the three memory categories, choose among framework paths, persist a LangGraph conversation with a checkpointer, resume a thread after a restart, isolate per-tier state with branches, and recall facts across threads with a semantic store.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31771","entityUrl":{"path":"/training/catalog/reverse-etl-with-lakebase-and-synced-tables-6342"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/reverse-etl-with-lakebase-and-synced-tables-6342"}}],"nid":31771,"vid":248392,"title":"Reverse ETL with Lakebase and Synced Tables","price":"75.00","duration":3600,"body":{"processed":"Moves Delta data into Lakebase for serving. Following the lecture-demo pattern, learners create synced tables in all three sync modes (snapshot, triggered, continuous), map Unity Catalog types to Postgres, verify propagation end to end, and assemble a three-mode strategy for a real workload mix.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31772","entityUrl":{"path":"/training/catalog/lakebase-postgres-to-lakehouse-change-data-feed-6344"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/lakebase-postgres-to-lakehouse-change-data-feed-6344"}}],"nid":31772,"vid":248393,"title":"Lakebase Postgres to Lakehouse Change Data Feed","price":"75.00","duration":3600,"body":{"processed":"Captures Lakebase changes back into Delta. Following the lecture-demo pattern, learners contrast Lakebase CDF with Delta CDF and synced tables, configure REPLICA IDENTITY FULL, interpret the five system columns in the destination Delta table, and choose among four downstream consumption patterns.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31773","entityUrl":{"path":"/training/catalog/databricks-apps-with-lakebase-6346"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-apps-with-lakebase-6346"}}],"nid":31773,"vid":248394,"title":"Databricks Apps with Lakebase","price":"75.00","duration":3600,"body":{"processed":"Ships a Lakebase-backed Databricks App. Following the lecture-demo pattern, learners scaffold a FastAPI app, wire its service principal identity into Lakebase with least-privilege grants, implement the OAuthConnection pattern with a shared pool, and deploy end to end — reasoning about read-your-writes and synced-table freshness along the way.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31774","entityUrl":{"path":"/training/catalog/serving-lakehouse-data-in-real-time-with-lakebase-6348"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/serving-lakehouse-data-in-real-time-with-lakebase-6348"}}],"nid":31774,"vid":248395,"title":"Serving Lakehouse Data in Real Time with Lakebase","price":"75.00","duration":3600,"body":{"processed":"Serves ML features from Lakebase on the hot path. Following the lecture-demo pattern, learners measure why Delta cannot serve single-row reads, read features from a synced table with millisecond point lookups, avoid the loop-vs-IN trap, reason about same-DB joins versus federation, and publish features to a managed online feature store.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31770","entityUrl":{"path":"/training/catalog/preparing-for-databricks-certification-exams-2683"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/preparing-for-databricks-certification-exams-2683"}}],"nid":31770,"vid":248391,"title":"Preparing for Databricks Certification Exams","price":"0.00","duration":1200,"body":{"processed":"Welcome to this course on preparing for your Databricks Certification exam. While most of the information found within this course is available on the Databricks Certification website, this training seeks to summarize that content to simplify your preparation.
Please note that this course will not teach any of the content on any particular exam.
Instead, this course will review the general information necessary for your test-taking experience to go as smoothly as possible, and point you to resources you can use to study for each exam.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31769","entityUrl":{"path":"/training/catalog/databricks-get-started-days-lakebase-ai-agents-6304"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-get-started-days-lakebase-ai-agents-6304"}}],"nid":31769,"vid":248389,"title":"Databricks Get Started Days (Lakebase + AI Agents)","price":"0.00","duration":14400,"body":{"processed":"Get Started with Lakebase
This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.
The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.
You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.
This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.
By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.
Get Started with AI Agents on Databricks
This course is an introduction to AI agents, their role in modern AI applications, and how to build AI agent applications on the Databricks platform. You'll learn about the principles of AI agents, how they differ from traditional AI systems, and explore their key components. Through interactive demos and hands-on labs, you'll see how to build, deploy, and evaluate AI agents on Databricks using Databricks AI and Agent Bricks. By the end of this course, you'll understand how to create and deploy AI agents using the Databricks Data + AI Platform.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31341","entityUrl":{"path":"/training/catalog/governing-lakebase-unity-catalog-postgres-6340"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/governing-lakebase-unity-catalog-postgres-6340"}}],"nid":31341,"vid":246953,"title":"Governing Lakebase: Unity Catalog + Postgres","price":"75.00","duration":3600,"body":{"processed":"Governs a Lakebase Postgres database with Unity Catalog without losing the Postgres access-control model underneath it. Following the lecture-demo pattern, learners start at the source with Postgres roles and the CONNECT to USAGE to table-grant ladder, add row-level security, register the database as a read-only UC foreign catalog, compare the Unity Catalog and Postgres permission models side by side (a federated read must satisfy both), then write a federated SELECT joining Lakebase and Delta and follow it through Catalog Explorer lineage and system.access.audit.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31337","entityUrl":{"path":"/training/catalog/working-with-data-in-lakebase-6337"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/working-with-data-in-lakebase-6337"}}],"nid":31337,"vid":246938,"title":"Working with Data in Lakebase","price":"75.00","duration":3600,"body":{"processed":"Tours the surfaces for working with data in Lakebase. Following the lecture-demo pattern, learners run queries in the SQL Editor, browse and edit rows and add indexes in the Tables view, connect from external clients and the PostgREST Data API, and query historical data through a point-in-time branch — choosing the right surface for each task and audience.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31102","entityUrl":{"path":"/training/catalog/lakebase-connection-and-authentication-patterns-6298"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/lakebase-connection-and-authentication-patterns-6298"}}],"nid":31102,"vid":246512,"title":"Lakebase Connection and Authentication Patterns","price":"75.00","duration":3600,"body":{"processed":"Makes Lakebase connections production-grade. Following the lecture-demo pattern, learners compare OAuth tokens and native passwords, handle the 60-minute token lifetime with refresh, and build a token-refreshing connection pool in both SQLAlchemy and raw psycopg — sized against the endpoint's connection ceiling and observed through pg_stat_activity. The course concludes with the Lakebase Data API, showing how the authenticator role brokers identity via SET ROLE to enforce the same privilege model over HTTP.
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"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31098","entityUrl":{"path":"/training/catalog/lakebase-branching-workflows-6300"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/lakebase-branching-workflows-6300"}}],"nid":31098,"vid":246486,"title":"Lakebase Branching Workflows","price":"75.00","duration":3600,"body":{"processed":"Turns copy-on-write branching into everyday practice. Following the lecture-demo pattern, learners create branches four ways, recover data with point-in-time branches, manage the branch lifecycle (protect, reset, delete), and choose a branching strategy with per-workload TTLs — including branch-per-PR CI/CD. Branches are the feature that lets developers pair a code branch with a database branch. Two real OrderOps admin apps, one bound to each branch, make isolation tangible: learners edit orders in each app and prove changes never cross branches, then graduate a schema change from the dev branch to production by re-running the migration and shipping the new app version.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31064","entityUrl":{"path":"/training/catalog/machine-learning-operations-2401"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-operations-2401"}}],"nid":31064,"vid":246240,"title":"Machine Learning Operations","price":"75.00","duration":10800,"body":{"processed":"This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.
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1. This is the fourth course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31063","entityUrl":{"path":"/training/catalog/machine-learning-operations-2400"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-operations-2400"}}],"nid":31063,"vid":246239,"title":"Machine Learning Operations","price":"0.00","duration":7200,"body":{"processed":"This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.
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1. This is the fourth course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"31042","entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-2343"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-2343"}}],"nid":31042,"vid":246097,"title":"Data Preparation for Machine Learning","price":"0.00","duration":7200,"body":{"processed":"This course focuses on the fundamentals of preparing data for machine learning using Databricks. Participants will learn essential skills for exploring, cleaning, and organizing data tailored for traditional machine learning applications. Key topics include data visualization, feature engineering, and optimal feature storage strategies. Through practical exercises, participants will gain hands-on experience in efficiently preparing data sets for machine learning within the Databricks. This course is designed for associate-level data scientists and machine learning practitioners. and individuals seeking to enhance their proficiency in data preparation, ensuring a solid foundation for successful machine learning model deployment.
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1. This is the first course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"31043","entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-2345"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-preparation-for-machine-learning-2345"}}],"nid":31043,"vid":246098,"title":"Data Preparation for Machine Learning","price":"75.00","duration":10800,"body":{"processed":"This course focuses on the fundamentals of preparing data for machine learning using Databricks. Participants will learn essential skills for exploring, cleaning, and organizing data tailored for traditional machine learning applications. Key topics include data visualization, feature engineering, and optimal feature storage strategies. Through practical exercises, participants will gain hands-on experience in efficiently preparing data sets for machine learning within the Databricks. This course is designed for associate-level data scientists and machine learning practitioners. and individuals seeking to enhance their proficiency in data preparation, ensuring a solid foundation for successful machine learning model deployment.
Note:
1. This is the first course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"31041","entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6273"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-end-to-end-6273"}}],"nid":31041,"vid":246090,"title":"Get Started with Databricks: End to End","price":"0.00","duration":7200,"body":{"processed":"This course is a comprehensive, hands-on introduction to the Databricks Data Intelligence Platform. You will follow a single end-to-end journey that starts in the workspace and finishes with an introduction to AI and machine learning, covering the everyday skills you need to work with data on Databricks.
The course covers:
• Navigating the Databricks workspace, compute options, and the Lakehouse versus Genie experiences.
• Understanding and ingesting data with Unity Catalog, including file upload and the Catalog Explorer.
• Working in Databricks notebooks and using Genie Code to write and debug code.
• Querying data with SQL, managing saved queries, and building dashboards and visualizations.
• Exploring data in natural language with Genie Agents.
• An introduction to AI and machine learning with MLflow and the Data Science Agent.
By the end of the course, you will be comfortable navigating Databricks, finding and governing data in Unity Catalog, writing SQL and notebook code with AI assistance, building dashboards, and exploring data with Genie.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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注意：对于 SCORM 讲授文件，请确保在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31038","entityUrl":{"path":"/training/catalog/sql-programming-and-procedural-logic-mandarin-chinese-6265"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/sql-programming-and-procedural-logic-mandarin-chinese-6265"}}],"nid":31038,"vid":246082,"title":"SQL Programming and Procedural Logic - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"在本课程中，您将在 Databricks 中探索核心 SQL 编程与过程逻辑技能，重点学习如何构建模块化、可维护且可用于生产的分析工作流。您将首先了解关键 SQL 构造——例如公用表表达式（包括高级递归 CTE）、会话作用域对象（如临时视图和临时表）以及用户定义函数——这些构造可使您的 SQL 开发更加简洁且可复用。随后，课程将引导您学习使用复合语句、变量、控制流、条件语句、循环以及完善的错误处理等高级 SQL 脚本编写技术，以创建结构化且灵活的 SQL 流程。您还将学习如何在这些多步骤管道中使用符合 ACID 规范的多语句事务来保证数据一致性。最后，您将了解如何将逻辑封装到 SQL 存储过程中，并使用 Lakeflow Jobs 和迁移策略编排复杂工作流，将遗留任务转换为模块化、自动化的管道，充分发挥 Databricks 平台的全部能力。
注意：对于 SCORM 讲授文件，请确保在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
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Languages Available: English | 日本語 | 한국어
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Languages Available: English | 日本語 | 한국어
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The course begins provides an overview of the main components of Databricks Apps, followed by the deployment of simple apps that integrates with an external service as well as a Databricks resource.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30858","entityUrl":{"path":"/training/catalog/aws-databricks-platform-administration-fundamentals-1514"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/aws-databricks-platform-administration-fundamentals-1514"}}],"nid":30858,"vid":244707,"title":"AWS Databricks Platform Administration Fundamentals","price":"0.00","duration":3600,"body":{"processed":"This course will provide you with a high-level overview of the AWS environment related to Databricks and covers details for administering the AWS Databricks Data Intelligence Platform. It will guide you through the configurations in the AWS Databricks Platform for setting up the environment for your organization."},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30859","entityUrl":{"path":"/training/catalog/aws-databricks-networking-and-security-fundamentals-1515"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/aws-databricks-networking-and-security-fundamentals-1515"}}],"nid":30859,"vid":244708,"title":"AWS Databricks Networking and Security Fundamentals","price":"0.00","duration":3600,"body":{"processed":"This course is designed to provide you with the essential details to customize the AWS Databricks environment’s structure and reinforce security at the infrastructural level."},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30860","entityUrl":{"path":"/training/catalog/aws-databricks-cloud-integrations-1517"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/aws-databricks-cloud-integrations-1517"}}],"nid":30860,"vid":244709,"title":"AWS Databricks Cloud Integrations","price":"0.00","duration":3600,"body":{"processed":"This course is designed to provide you with the essential details to integrate the Databricks Platform with AWS services.The AWS services covered in this course are S3,Kinesis,Redshift and Bedrock.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30855","entityUrl":{"path":"/training/catalog/gcp-databricks-platform-administration-fundamentals-1744"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/gcp-databricks-platform-administration-fundamentals-1744"}}],"nid":30855,"vid":244703,"title":"GCP Databricks Platform Administration Fundamentals","price":"0.00","duration":3600,"body":{"processed":"This course will provide you with a high level overview of the GCP environment related to Databricks and covers details for administering the GCP Databricks data intelligence platform. It will guide you through the configurations in the GCP Databricks Platform for setting up the environment for your organization."},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30840","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-mandarin-chinese-5576"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-mandarin-chinese-5576"}}],"nid":30840,"vid":244567,"title":"Get Started with Databricks for Machine Learning - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"在本课程中，您将培养使用 Databricks Data Intelligence Platform 执行机器学习工作流并支持数据科学工作负载所需的基础技能。您将从机器学习从业者的视角探索该平台，内容涵盖使用 Mosaic AI Feature Engineering 构建和管理特征、使用 MLflow 进行端到端模型生命周期管理，以及使用 Lakeflow Jobs 进行管道编排等主题。此外，您还将学习如何使用 Databricks AI Model Serving 进行实时模型推理，并通过 Genie Code - Data Science Agent Mode 体验 Databricks 透明、对话式的模型开发方式——在其中，您可以使用自然语言提示，直接在笔记本中生成、运行并迭代优化可执行的 ML 工作流。本课程包含由讲师主导的演示，并以一个全面的实验作为收尾，巩固贯穿全程所讲解的概念。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30841","entityUrl":{"path":"/training/catalog/get-started-with-lakebase-mandarin-chinese-5878"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-lakebase-mandarin-chinese-5878"}}],"nid":30841,"vid":244568,"title":"Get Started with Lakebase - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"这门入门课程介绍 Databricks Lakebase，这是一项内置于 Databricks Data Intelligence Platform 的完全托管的 PostgreSQL 服务，它让运营型（OLTP）和分析型（OLAP）工作负载更加紧密地结合在一起。
课程以一节概念讲座开始，对比 OLTP 和 OLAP 系统，讲解它们不同的性能特征、存储模型和典型用例。你还将探讨组织在维护相互独立的事务型数据库和分析平台时所面临的挑战，包括数据移动、延迟和架构复杂性。
随后你将学习 Databricks Lakebase 如何通过提供一个与 Databricks Lakehouse 直接集成、PostgreSQL 兼容的运营型数据库来应对这些挑战，使运营型应用和分析能够在一个统一平台内协同工作。
通过动手实验，你将：
使用 autoscaling compute 创建并探索一个 Lakebase 项目
• 浏览 Lakebase UI，包括 branching、监控和配置设置
• 使用 Lakebase SQL Editor 创建并查询表
• 使用 Lakehouse Federation 和外部目录从 Databricks 查询 Lakebase 数据
• 通过将 Delta 表同步到 Lakebase 来执行 Reverse ETL
• 从 Python 连接到 Lakebase 并执行基本的 CRUD 操作
这是一门入门（Get Started）课程，因此重点在于理解使用 Lakebase 的核心概念和基本工作流。在 Lakebase 之上构建完整的生产应用不在本课程的范围之内。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30842","entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-mandarin-chinese-5879"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-mandarin-chinese-5879"}}],"nid":30842,"vid":244569,"title":"Get Started with Databricks Platform Administration - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"在本课程中，你将学习在 Databricks Data Intelligence Platform 上进行平台管理的基础知识。本课程全面概述 Unity Catalog——在 Databricks 环境中实现有效数据治理的关键组件。课程分为五个模块，首先详细介绍 Databricks 基础架构及其数据智能平台，包括对 Databricks Workspace 的深入演练。你将探讨 Unity Catalog 中的数据治理原则，涵盖其关键概念、架构和角色。课程进一步强调对 Unity Catalog 元存储和 compute 资源（包括集群和 SQL 仓库）的管理。最后，你将通过学习权限、细粒度访问以及如何治理数据对象来掌握数据访问控制。课程结束时，你将掌握管理 Unity Catalog 所需的核心技能，以实施有效的数据治理、优化 compute 资源并落实稳健的数据安全策略。如购买 Databricks Labs 订阅，本课程还会以一个综合实验练习收尾，让你在真实的 Databricks Workspace 环境中实践所学内容。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30764","entityUrl":{"path":"/training/catalog/get-started-with-lakebase-5081"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-lakebase-5081"}}],"nid":30764,"vid":243839,"title":"Get Started with Lakebase","price":"0.00","duration":7200,"body":{"processed":"This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.
The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.
You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.
This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.
By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30747","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-2724"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-2724"}}],"nid":30747,"vid":241565,"title":"Get Started with Databricks for Generative AI","price":"0.00","duration":7200,"body":{"processed":"This course offers a practical introduction to the Databricks Data Intelligence Platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore tools such as AI Search, the Agent Framework, and MLflow's generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications on the Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30746","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-3480"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-generative-ai-3480"}}],"nid":30746,"vid":241516,"title":"Get Started with Databricks for Generative AI","price":"75.00","duration":10800,"body":{"processed":"This course offers a practical introduction to the Databricks Data Intelligence Platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore tools such as AI Search, the Agent Framework, and MLflow's generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications on the Databricks Data Intelligence Platform.
\nLanguages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30745","entityUrl":{"path":"/training/catalog/lakehouse-architecture-fundamentals-mandarin-chinese-6088"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/lakehouse-architecture-fundamentals-mandarin-chinese-6088"}}],"nid":30745,"vid":241431,"title":"Lakehouse Architecture Fundamentals - Mandarin Chinese","price":"0.00","duration":3600,"body":{"processed":"这是一门基于《The Data Lakehouse For Dummies》的概念性课程。课程引导学习者从\"不了解湖仓是什么\"，逐步达到能够就湖仓架构及其背后技术进行深入交流的水平，内容涵盖：传统架构的局限性、湖仓的定义、其核心技术，以及它如何在 Databricks 上实现数据智能与统一工作负载。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30704","entityUrl":{"path":"/training/catalog/get-started-with-ai-agents-on-databricks-4464"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-ai-agents-on-databricks-4464"}}],"nid":30704,"vid":241192,"title":"Get Started with AI Agents on Databricks","price":"0.00","duration":7200,"body":{"processed":"This course is an introduction to AI agents, their role in modern AI applications, and how to build AI agent applications on the Databricks platform. You'll learn about the principles of AI agents, how they differ from traditional AI systems, and explore their key components. Through interactive demos and hands-on labs, you'll see how to build, deploy, and evaluate AI agents on Databricks using Databricks AI and Agent Bricks. By the end of this course, you'll understand how to create and deploy AI agents using the Databricks Data + AI Platform.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30671","entityUrl":{"path":"/training/catalog/introduction-to-python-for-data-science-and-data-engineering-1211"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/introduction-to-python-for-data-science-and-data-engineering-1211"}}],"nid":30671,"vid":239184,"title":"Introduction to Python for Data Science and Data Engineering","price":"0.00","duration":18000,"body":{"processed":"This course is intended for complete beginners to Python to provide the basics of programmatically interacting with data. The course begins with a basic introduction to programming expressions, variables, and data types. It then progresses into conditional and control statements, functions, collection types, loops, error handling, and classes. You will learn to extend Python with external libraries and gain experience using the pandas library for data analysis and visualization, including scaling pandas workflows with Apache Spark. Lastly, you will explore the fundamentals of cloud computing. Throughout the course, you will gain hands-on practice through lab exercises, with additional resources to deepen your knowledge of programming after the class.
Last course update
Aug 2026
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30672","entityUrl":{"path":"/training/catalog/introduction-to-python-for-data-science-and-data-engineering-1874"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/introduction-to-python-for-data-science-and-data-engineering-1874"}}],"nid":30672,"vid":239185,"title":"Introduction to Python for Data Science and Data Engineering","price":"75.00","duration":36000,"body":{"processed":"This course is intended for complete beginners to Python to provide the basics of programmatically interacting with data. The course begins with a basic introduction to programming expressions, variables, and data types. It then progresses into conditional and control statements, functions, collection types, loops, error handling, and classes. You will learn to extend Python with external libraries and gain experience using the pandas library for data analysis and visualization, including scaling pandas workflows with Apache Spark. Lastly, you will explore the fundamentals of cloud computing. Throughout the course, you will gain hands-on practice through lab exercises, with additional resources to deepen your knowledge of programming after the class.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2409,"name":"Docebo"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30603","entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-2453"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-2453"}}],"nid":30603,"vid":238683,"title":"Get Started with Databricks Platform Administration","price":"0.00","duration":7200,"body":{"processed":"In this course, you will learn the basics of platform administration on the Databricks Data Intelligence Platform. It offers a comprehensive overview of the Unity Catalog, a vital component for effective data governance within Databricks environments. Divided into five modules, it begins with a detailed introduction to Databricks infrastructure and its data intelligence platform, including an in-depth walkthrough of the Databricks Workspace. You will explore data governance principles within Unity Catalog, covering its key concepts, architecture, and roles. The course further emphasizes managing Unity Catalog metastores and compute resources, including clusters and SQL warehouses. Finally, you'll master data access control by learning about privileges, fine-grained access, and how to govern data objects. By the end, you will be equipped with essential skills to administer the Unity Catalog to implement effective data governance, optimize compute resources, and enforce robust data security strategies.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30604","entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-2454"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-platform-administration-2454"}}],"nid":30604,"vid":238684,"title":"Get Started with Databricks Platform Administration","price":"75.00","duration":10800,"body":{"processed":"In this course, you will learn the basics of platform administration on the Databricks Data Intelligence Platform. It offers a comprehensive overview of the Unity Catalog, a vital component for effective data governance within Databricks environments. Divided into five modules, it begins with a detailed introduction to Databricks infrastructure and its data intelligence platform, including an in-depth walkthrough of the Databricks Workspace. You will explore data governance principles within Unity Catalog, covering its key concepts, architecture, and roles. The course further emphasizes managing Unity Catalog metastores and compute resources, including clusters and SQL warehouses. Finally, you'll master data access control by learning about privileges, fine-grained access, and how to govern data objects. By the end, you will be equipped with essential skills to administer the Unity Catalog to implement effective data governance, optimize compute resources, and enforce robust data security strategies. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"30594","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-2460"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-2460"}}],"nid":30594,"vid":238562,"title":"Get Started with Databricks for Machine Learning","price":"0.00","duration":7200,"body":{"processed":"In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data science and machine learning workflow. You will be given a tour of the workspace, and you will be shown how to work with notebooks. You will explore exploratory data analysis and feature engineering, track and manage models with MLflow, experiment using Databricks Genie Code, and deploy a model with Databricks Model Serving. Finally, the course brings these skills together in a comprehensive lab covering the end-to-end machine learning.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"30595","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-2461"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-2461"}}],"nid":30595,"vid":238563,"title":"Get Started with Databricks for Machine Learning","price":"75.00","duration":10800,"body":{"processed":"In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data science and machine learning workflow. You will be given a tour of the workspace, and you will be shown how to work with notebooks. You will explore exploratory data analysis and feature engineering, track and manage models with MLflow, experiment using Databricks Genie Code, and deploy a model with Databricks Model Serving. Finally, the course brings these skills together in a comprehensive lab covering the end-to-end machine learning.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"30470","entityUrl":{"path":"/training/catalog/sql-analytics-on-databricks-3928"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/sql-analytics-on-databricks-3928"}}],"nid":30470,"vid":237970,"title":"SQL Analytics on Databricks","price":"0.00","duration":7200,"body":{"processed":"In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights.
You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.
Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"30469","entityUrl":{"path":"/training/catalog/sql-analytics-on-databricks-3925"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/sql-analytics-on-databricks-3925"}}],"nid":30469,"vid":237969,"title":"SQL Analytics on Databricks","price":"75.00","duration":10800,"body":{"processed":"In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights.
You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.
Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
A concept-level course based on The Data Lakehouse For Dummies. It moves learners from \"not sure what a lakehouse is\" to being able to hold a working conversation about lakehouse architecture and the technologies behind it: the limitations of legacy architectures, what the lakehouse is, its core technologies, and how it enables data intelligence and unified workloads on Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30377","entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-3347"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-3347"}}],"nid":30377,"vid":237155,"title":"Get Started with SQL Analytics and BI on Databricks","price":"0.00","duration":7200,"body":{"processed":"This course introduces the Databricks Data Intelligence Platform and the core skills a data analyst needs for day-to-day SQL analytics and BI work. You'll navigate the workspace and Unity Catalog, write SQL queries against Unity Catalog managed tables from a Serverless SQL Warehouse, use Genie Code to generate and debug SQL, work with Delta Lake (DML, version history, time travel, and restore), build and publish AI/BI Dashboards, and create Genie Agents for conversational analytics.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"30378","entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-3350"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-3350"}}],"nid":30378,"vid":237156,"title":"Get Started with SQL Analytics and BI on Databricks","price":"75.00","duration":10800,"body":{"processed":"This course introduces the Databricks Data Intelligence Platform and the core skills a data analyst needs for day-to-day SQL analytics and BI work. You'll navigate the workspace and Unity Catalog, write SQL queries against Unity Catalog managed tables from a Serverless SQL Warehouse, use Genie Code to generate and debug SQL, work with Delta Lake (DML, version history, time travel, and restore), build and publish AI/BI Dashboards, and create Genie Agents for conversational analytics.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"30354","entityUrl":{"path":"/training/catalog/aibi-for-data-analysts-mandarin-chinese-5956"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/aibi-for-data-analysts-mandarin-chinese-5956"}}],"nid":30354,"vid":236971,"title":"AI/BI for Data Analysts - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程面向数据分析师，讲授如何在 Databricks 中设计、构建、发布和运维 AI/BI Dashboards。AI/BI Dashboards 将受 Unity Catalog 治理的数据与交互式可视化、筛选器和 Genie 集成相结合，使业务用户无需编写代码即可探索答案。
本课程围绕一个端到端构建项目展开。您将从 Unity Catalog 中的源表开始，最终完成一个已发布、受监控的多页面仪表盘。在此过程中，您将了解仪表盘如何融入更广泛的 Databricks AI/BI 产品系列，以及 Genie、数据集、可视化和筛选器在工作流中的各自作用。
课程内容包括：
• AI/BI Dashboard 基础知识，以及它与 Genie 和 Databricks 平台其他部分的关系。
• 探索 Unity Catalog 中的源数据，并使用 SQL 设计可复用的仪表盘数据集。
• 创建可视化（KPI、趋势和细分），并设计简洁的多页面仪表盘布局。
• 使用 Genie Code，根据自然语言提示词起草 SQL、图表和筛选器。
• 添加筛选器，使仪表盘能够进行交互并响应查看者的问题。
• 发布和共享仪表盘并管理权限，确保适当的人员可以查看和编辑仪表盘。
• 通过定时刷新、缓存和使用情况监控，在生产环境中运行仪表盘。
注意：对于 SCORM 讲授文件，请确保在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
本课程面向数据分析师，讲授如何在 Databricks 中设计、构建、发布和运维 AI/BI Dashboards。AI/BI Dashboards 将受 Unity Catalog 治理的数据与交互式可视化、筛选器和 Genie 集成相结合，使业务用户无需编写代码即可探索答案。
本课程围绕一个端到端构建项目展开。您将从 Unity Catalog 中的源表开始，最终完成一个已发布、受监控的多页面仪表盘。在此过程中，您将了解仪表盘如何融入更广泛的 Databricks AI/BI 产品系列，以及 Genie、数据集、可视化和筛选器在工作流中的各自作用。
课程内容包括：
• AI/BI Dashboard 基础知识，以及它与 Genie 和 Databricks 平台其他部分的关系。
• 探索 Unity Catalog 中的源数据，并使用 SQL 设计可复用的仪表盘数据集。
• 创建可视化（KPI、趋势和细分），并设计简洁的多页面仪表盘布局。
• 使用 Genie Code，根据自然语言提示词起草 SQL、图表和筛选器。
• 添加筛选器，使仪表盘能够进行交互并响应查看者的问题。
• 发布和共享仪表盘并管理权限，确保适当的人员可以查看和编辑仪表盘。
• 通过定时刷新、缓存和使用情况监控，在生产环境中运行仪表盘。
注意：对于 SCORM 讲授文件，请确保在完成内容后关闭 SCORM 窗口。请勿点击“Next Lesson”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"30356","entityUrl":{"path":"/training/catalog/generative-ai-engineering-with-databricks-spanish-6002"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/generative-ai-engineering-with-databricks-spanish-6002"}}],"nid":30356,"vid":236973,"title":"Generative AI Engineering with Databricks - Spanish","price":"1500.00","duration":57600,"body":{"processed":"Este curso está dirigido a científicos de datos, ingenieros de machine learning y otros profesionales de datos que desean crear aplicaciones de IA generativa utilizando los frameworks más recientes y populares y las funcionalidades de Databricks.
Nota: Databricks Academy está migrando a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, y deja de utilizar diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
A continuación, describimos cada uno de los cuatro módulos de cuatro horas incluidos en este curso.
Building RAG Agents with Agent Bricks: este curso ofrece capacitación práctica para crear agentes de recuperación utilizando Databricks Agent Bricks. Los participantes aprenderán a explorar y consultar Knowledge Assistants, analizar documentos no estructurados para convertirlos en datos estructurados mediante AI Functions, dividir texto en fragmentos (chunks) para la recuperación semántica, crear índices de Vector Search y crear Knowledge Assistants listos para producción respaldados por múltiples fuentes de conocimiento.
Building Agentic Applications on Databricks: este curso enseña a los estudiantes a crear aplicaciones agénticas de nivel de producción en Databricks. Los estudiantes aprenden a crear herramientas de agente gobernadas mediante Unity Catalog y MCP, crear sistemas de agente único y multiagente con el OpenAI Agents SDK, y aprovechar Agent Bricks y Genie para casos de uso de knowledge assistant orquestados con un agente supervisor. El curso abarca toda la progresión, desde la creación de prototipos de herramientas hasta la implementación en producción, con experiencia práctica utilizando el rastreo (tracing) de MLflow para observar la ejecución del agente.
Agent Evaluation on Databricks: este curso enseña a los estudiantes a evaluar sistemáticamente agentes de IA utilizando el framework de evaluación de MLflow, abordando los desafíos únicos de los sistemas de IA no deterministas que las pruebas de software tradicionales no pueden manejar. Los estudiantes aprenden a implementar diversos enfoques de evaluación, incluidos los jueces integrados (built-in judges) para criterios comunes como la corrección y la seguridad, los jueces basados en directrices para requisitos específicos del negocio y los jueces personalizados para necesidades especializadas. El curso abarca tanto la evaluación sin conexión utilizando conjuntos de datos (datasets) seleccionados como el monitoreo de producción en línea, con experiencia práctica utilizando las capacidades de rastreo (tracing) de MLflow para comprender los patrones de ejecución del agente y recopilar retroalimentación humana de diferentes tipos de partes interesadas. A través de demostraciones y laboratorios prácticos, los estudiantes desarrollan habilidades para crear flujos de trabajo de evaluación que impulsan mejoras continuas de calidad a lo largo del ciclo de vida de desarrollo de los agentes de IA.
Deploying and Monitoring Agent Applications on Databricks: este curso abarca el ciclo de vida completo para implementar y monitorear agentes de IA generativa en Databricks. Los participantes aprenderán a implementar agentes como Databricks Apps utilizando Declarative Automation Bundles (DABs), integrar herramientas mediante el Model Context Protocol (MCP), instrumentar agentes con MLflow Tracing y evaluar la calidad en producción utilizando scorers, jueces de múltiples turnos y evaluación en línea. A través de demos y laboratorios prácticos, los participantes adquirirán experiencia práctica en la creación, observación y monitoreo de agentes de IA de nivel de producción en la plataforma Databricks.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30357","entityUrl":{"path":"/training/catalog/generative-ai-engineering-with-databricks-french-6006"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/generative-ai-engineering-with-databricks-french-6006"}}],"nid":30357,"vid":236974,"title":"Generative AI Engineering with Databricks - French","price":"1500.00","duration":57600,"body":{"processed":"Ce cours s’adresse aux data scientists, aux ingénieurs en machine learning et aux autres professionnels des données qui souhaitent créer des applications d’IA générative à l’aide des frameworks les plus récents et les plus populaires et des fonctionnalités de Databricks.
Remarque : Databricks Academy passe à un format basé sur des notebooks pour les sessions en classe dans l’environnement Databricks, et n’utilise plus de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l’environnement de laboratoire Vocareum.
Ci-dessous, nous décrivons chacun des quatre modules de quatre heures inclus dans ce cours.
Building RAG Agents with Agent Bricks : ce cours propose une formation pratique à la création d’agents de récupération à l’aide de Databricks Agent Bricks. Les participants apprendront à explorer et à interroger les Knowledge Assistants, à analyser des documents non structurés pour les convertir en données structurées à l’aide des AI Functions, à découper le texte en fragments (chunks) pour la récupération sémantique, à créer des index Vector Search et à créer des Knowledge Assistants prêts pour la production s’appuyant sur plusieurs sources de connaissances.
Building Agentic Applications on Databricks : ce cours enseigne aux étudiants comment créer des applications agentiques de niveau production sur Databricks. Les étudiants apprennent à créer des outils d’agent gouvernés à l’aide d’Unity Catalog et de MCP, à créer des systèmes à agent unique et multi-agents avec l’OpenAI Agents SDK, et à exploiter Agent Bricks et Genie pour des cas d’usage de knowledge assistant orchestrés avec un agent superviseur. Le cours couvre l’ensemble de la progression, du prototypage des outils au déploiement en production, avec une expérience pratique de l’utilisation du traçage (tracing) MLflow pour observer l’exécution des agents.
Agent Evaluation on Databricks : ce cours enseigne aux étudiants comment évaluer systématiquement les agents IA à l’aide du cadre d’évaluation de MLflow, en relevant les défis propres aux systèmes d’IA non déterministes que les tests logiciels traditionnels ne peuvent pas gérer. Les étudiants apprennent à mettre en œuvre diverses approches d’évaluation, notamment les juges intégrés (built-in judges) pour des critères courants tels que l’exactitude et la sécurité, les juges basés sur des directives pour des exigences propres à l’entreprise, et les juges personnalisés pour des besoins spécialisés. Le cours couvre à la fois l’évaluation hors ligne à l’aide d’ensembles de données (datasets) sélectionnés et la surveillance de la production en ligne, avec une expérience pratique de l’utilisation des capacités de traçage (tracing) de MLflow pour comprendre les schémas d’exécution des agents et recueillir les retours humains de différents types de parties prenantes. Grâce à des démonstrations et des laboratoires pratiques, les étudiants développent des compétences pour créer des flux de travail d’évaluation qui favorisent l’amélioration continue de la qualité tout au long du cycle de vie de développement des agents IA.
Deploying and Monitoring Agent Applications on Databricks : ce cours couvre le cycle de vie de bout en bout pour le déploiement et la surveillance des agents d’IA générative sur Databricks. Les participants apprendront à déployer des agents en tant que Databricks Apps à l’aide des Declarative Automation Bundles (DABs), à intégrer des outils via le Model Context Protocol (MCP), à instrumenter les agents avec MLflow Tracing, et à évaluer la qualité en production à l’aide de scorers, de juges multi-tours et de l’évaluation en ligne. Grâce à des démos et des laboratoires pratiques, les participants acquerront une expérience pratique de la création, de l’observation et de la surveillance d’agents IA de niveau production sur la plateforme Databricks.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30328","entityUrl":{"path":"/training/catalog/generative-ai-fundamentals-accreditation-mandarin-chinese-5949"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/generative-ai-fundamentals-accreditation-mandarin-chinese-5949"}}],"nid":30328,"vid":236722,"title":"Generative AI Fundamentals Accreditation - Mandarin Chinese","price":"0.00","duration":900,"body":{"processed":"欢迎参加 Databricks Generative AI Fundamentals - 认证考核
这是一项 20 分钟的评估，将检验您对生成式 AI 相关基本概念的了解。
成功完成本次评估后，您将获得 Databricks Generative AI Fundamentals 徽章。
学习路径
• 本认证是 Databricks Generative AI Fundamentals 学习计划的一部分。
完成证明
• 达到 80% 的通过率后，您将获得 Databricks 颁发的徽章。
Languages Available: English | 日本語 | Português BR
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29847","entityUrl":{"path":"/training/catalog/automated-deployment-with-declarative-automation-bundles-3489"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/automated-deployment-with-declarative-automation-bundles-3489"}}],"nid":29847,"vid":235422,"title":"Automated Deployment with Declarative Automation Bundles","price":"0.00","duration":7200,"body":{"processed":"This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.
The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.
Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.
Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is the fourth in the 'Advanced Data Engineering with Databricks' series.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29848","entityUrl":{"path":"/training/catalog/automated-deployment-with-declarative-automation-bundles-3724"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/automated-deployment-with-declarative-automation-bundles-3724"}}],"nid":29848,"vid":235424,"title":"Automated Deployment with Declarative Automation Bundles","price":"75.00","duration":10800,"body":{"processed":"This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.
The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.
Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.
Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is the fourth in the 'Advanced Data Engineering with Databricks' series.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29763","entityUrl":{"path":"/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-3125"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-3125"}}],"nid":29763,"vid":234465,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI)","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.
Get Started with SQL Analytics and BI on Databricks
In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data analytics workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with data objects in Databricks such as catalogs, schemas, tables, compute clusters, notebooks, and dashboards. You will then follow a basic data analytics workflow to perform tasks such as manipulating data using Databricks SQL, leveraging Delta Lake version logs to time travel, creating dashboards within the platform, and creating Genie Spaces for data exploration using natural language prompts. You will also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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Get Started with Databricks for Generative AI
This course offers a practical introduction to the Mosaic AI platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore Mosaic AI tools such as Vector Search, the Agent Framework, and MLflow’s generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications using Mosaic AI.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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In this course, you will explore the Databricks Data Intelligence Platform from the perspective of platform architecture, specifically related to the platform foundation in lakehouse architecture. You will learn about the scope, vision, and capabilities of a platform founded in lakehouse architecture, with a focus on how Databricks integrates with a cloud platform’s architecture. You’ll learn about the key features of a successful lakehouse implementation, specifically how to adhere to the well-architected lakehouse framework, which emphasizes structural excellence through specific dimensions, principles and best practices. You’ll also learn about data architecture strategy for the acceleration of data and AI endeavors.
Get Started with Databricks for Data Warehousing
This course provides a comprehensive overview of Databricks’ modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks.
This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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Get Started with Databricks for Machine Learning
In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing basic machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as feature engineering with Databricks Notebooks and model lifecycle tracking with MLflow. Additionally, you will learn about real-time model inference with Mosaic AI Model Serving and experience Databricks’ “glass box” approach to model development through AutoML. The course includes three instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered in the demos.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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Languages Available: English | 日本語 | Português BR | 한국어
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"29623","entityUrl":{"path":"/training/catalog/building-agentic-applications-on-databricks-5847"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-agentic-applications-on-databricks-5847"}}],"nid":29623,"vid":234129,"title":"Building Agentic Applications on Databricks","price":"75.00","duration":10800,"body":{"processed":"This course teaches students how to build production-grade agentic applications on Databricks. Students learn to create governed agent tools using Unity Catalog and MCP, build single and multi-agent systems with the OpenAI Agents SDK, and leverage Agent Bricks and Genie for knowledge-assistant use cases orchestrated with a supervisor agent. The course covers the full progression from tool prototyping to production deployment, with hands-on experience using MLflow tracing to observe agent execution.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29624","entityUrl":{"path":"/training/catalog/building-rag-agents-with-agent-bricks-5848"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-rag-agents-with-agent-bricks-5848"}}],"nid":29624,"vid":234130,"title":"Building RAG Agents with Agent Bricks","price":"75.00","duration":10800,"body":{"processed":"This course provides hands-on training for building retrieval agents using Databricks Agent Bricks. Participants will learn to explore and query Knowledge Assistants, parse unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, build Vector Search indexes, and create production-ready Knowledge Assistants backed by multiple knowledge sources.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29625","entityUrl":{"path":"/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-5855"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-5855"}}],"nid":29625,"vid":234131,"title":"Deploying and Monitoring Agent Applications on Databricks","price":"0.00","duration":7200,"body":{"processed":"This course covers the end-to-end lifecycle for deploying and monitoring generative AI agents on Databricks. Participants will learn how to deploy agents as Databricks Apps using Declarative Automation Bundles (DABs), integrate tools via the Model Context Protocol (MCP), instrument agents with MLflow Tracing, and evaluate production quality using scorers, multi-turn judges, and online evaluation. Through hands-on demos and labs, participants will gain practical experience building, observing, and monitoring production-grade AI agents on the Databricks platform.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"29626","entityUrl":{"path":"/training/catalog/building-agentic-applications-on-databricks-5856"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-agentic-applications-on-databricks-5856"}}],"nid":29626,"vid":234132,"title":"Building Agentic Applications on Databricks","price":"0.00","duration":7200,"body":{"processed":"This course teaches students how to build production-grade agentic applications on Databricks. Students learn to create governed agent tools using Unity Catalog and MCP, build single and multi-agent systems with the OpenAI Agents SDK, and leverage Agent Bricks and Genie for knowledge-assistant use cases orchestrated with a supervisor agent. The course covers the full progression from tool prototyping to production deployment, with hands-on experience using MLflow tracing to observe agent execution.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29627","entityUrl":{"path":"/training/catalog/building-rag-agents-with-agent-bricks-5857"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-rag-agents-with-agent-bricks-5857"}}],"nid":29627,"vid":234133,"title":"Building RAG Agents with Agent Bricks","price":"0.00","duration":7200,"body":{"processed":"This course provides hands-on training for building retrieval agents using Databricks Agent Bricks. Participants will learn to explore and query Knowledge Assistants, parse unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, build Vector Search indexes, and create production-ready Knowledge Assistants backed by multiple knowledge sources.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29634","entityUrl":{"path":"/training/catalog/get-started-with-lakebase-mandarin-chinese-5877"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-lakebase-mandarin-chinese-5877"}}],"nid":29634,"vid":234140,"title":"Get Started with Lakebase - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"这门入门课程介绍 Databricks Lakebase，这是一项内置于 Databricks Data Intelligence Platform 的完全托管的 PostgreSQL 服务，它让运营型（OLTP）和分析型（OLAP）工作负载更加紧密地结合在一起。
课程以一节概念讲座开始，对比 OLTP 和 OLAP 系统，讲解它们不同的性能特征、存储模型和典型用例。你还将探讨组织在维护相互独立的事务型数据库和分析平台时所面临的挑战，包括数据移动、延迟和架构复杂性。
随后你将学习 Databricks Lakebase 如何通过提供一个与 Databricks Lakehouse 直接集成、PostgreSQL 兼容的运营型数据库来应对这些挑战，使运营型应用和分析能够在一个统一平台内协同工作。
通过动手实验，你将：
使用 autoscaling compute 创建并探索一个 Lakebase 项目
• 浏览 Lakebase UI，包括 branching、监控和配置设置
• 使用 Lakebase SQL Editor 创建并查询表
• 使用 Lakehouse Federation 和外部目录从 Databricks 查询 Lakebase 数据
• 通过将 Delta 表同步到 Lakebase 来执行 Reverse ETL
• 从 Python 连接到 Lakebase 并执行基本的 CRUD 操作
这是一门入门（Get Started）课程，因此重点在于理解使用 Lakebase 的核心概念和基本工作流。在 Lakebase 之上构建完整的生产应用不在本课程的范围之内。
注意：对于 SCORM 课程文件，请在完成内容后关闭 SCORM 窗口。请勿点击“下一课”按钮，否则可能导致 SCORM 模块无法被标记为已完成。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29461","entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-2963"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-2963"}}],"nid":29461,"vid":232993,"title":"Data Ingestion with Lakeflow Connect","price":"0.00","duration":7200,"body":{"processed":"This course provides a comprehensive introduction to Lakeflow Connect, a scalable and simplified solution for ingesting data into Databricks from a wide range of sources. You’ll begin by exploring the different types of Lakeflow Connect connectors (Standard and Managed) and learn various data ingestion techniques, including batch, incremental batch, and streaming ingestion. You'll also review the key benefits of using UC table and the Medallion architecture
Next, you’ll develop practical skills for ingesting data from cloud object storage using Lakeflow Connect Standard Connectors. This includes working with methods such as CREATE TABLE AS SELECT (CTAS), COPY INTO, and Auto Loader, with an emphasis on the benefits and considerations of each approach. You’ll also learn how to append metadata columns to your bronze-level tables during ingestion into the Databricks Data Intelligence Platform. The course then covers how to handle records that don’t match your table schema using the rescued data column, along with strategies for managing and analyzing this data. You’ll also explore techniques for ingesting and flattening semi-structured JSON data.
Following this, you’ll explore how to perform enterprise-grade data ingestion using Lakeflow Connect Managed Connectors to bring in data from databases and Software-as-a-Service (SaaS) applications. The course also introduces Partner Connect as an option for integrating partner tools into your ingestion workloads.
Finally, the course wraps up with alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with a strong foundation to support modern data engineering use cases.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29451","entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-2968"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-ingestion-with-lakeflow-connect-2968"}}],"nid":29451,"vid":232903,"title":"Data Ingestion with Lakeflow Connect","price":"75.00","duration":10800,"body":{"processed":"This course provides a comprehensive introduction to Lakeflow Connect, a scalable and simplified solution for ingesting data into Databricks from a wide range of sources. You’ll begin by exploring the different types of Lakeflow Connect connectors (Standard and Managed) and learn various data ingestion techniques, including batch, incremental batch, and streaming ingestion. You'll also review the key benefits of using UC table and the Medallion architecture
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Following this, you’ll explore how to perform enterprise-grade data ingestion using Lakeflow Connect Managed Connectors to bring in data from databases and Software-as-a-Service (SaaS) applications. The course also introduces Partner Connect as an option for integrating partner tools into your ingestion workloads.
Finally, the course wraps up with alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with a strong foundation to support modern data engineering use cases.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29426","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-mandarin-chinese-5767"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-mandarin-chinese-5767"}}],"nid":29426,"vid":232526,"title":"Get Started with Databricks for Data Engineering - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程介绍在 Databricks Data Intelligence Platform 上执行基础数据工程工作流所需的核心技能。您将探索工作区、使用 Unity Catalog，并学习数据工程师在 Databricks 上日常使用的基础构建模块。
本课程采用实操方式。您首先熟悉工作区，然后针对每个主题完成配套的演示（Demo）和实验（Lab）笔记本。演示会由讲师或引导式笔记本带您了解某个概念；实验则要求您自行应用刚刚所学的内容。
课程内容涵盖：
• Databricks Data Intelligence Platform，以及 Databricks 工作区、Unity Catalog 和笔记本如何协同运作。
• 创建和管理 Delta Lake 表。
• 使用 INSERT、UPDATE 和 DELETE 修改数据。
• 探索 Delta 表的版本历史记录和时间旅行。
• 使用 Lakeflow Connect 选项（CTAS、上传 UI 和 COPY INTO）引入数据。
• 构建奖牌架构管道，通过 Bronze、Silver 和 Gold 层转换数据。
• 使用 Lakeflow Jobs 实现管道自动化。
•（附加内容）使用 Spark Declarative Pipelines 构建声明式管道。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29427","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-mandarin-chinese-5768"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-mandarin-chinese-5768"}}],"nid":29427,"vid":232527,"title":"Get Started with Databricks for Data Engineering - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"本课程介绍在 Databricks Data Intelligence Platform 上执行基础数据工程工作流所需的核心技能。您将探索工作区、使用 Unity Catalog，并学习数据工程师在 Databricks 上日常使用的基础构建模块。
本课程采用实操方式。您首先熟悉工作区，然后针对每个主题完成配套的演示（Demo）和实验（Lab）笔记本。演示会由讲师或引导式笔记本带您了解某个概念；实验则要求您自行应用刚刚所学的内容。
课程内容涵盖：
• Databricks Data Intelligence Platform，以及 Databricks 工作区、Unity Catalog 和笔记本如何协同运作。
• 创建和管理 Delta Lake 表。
• 使用 INSERT、UPDATE 和 DELETE 修改数据。
• 探索 Delta 表的版本历史记录和时间旅行。
• 使用 Lakeflow Connect 选项（CTAS、上传 UI 和 COPY INTO）引入数据。
• 构建奖牌架构管道，通过 Bronze、Silver 和 Gold 层转换数据。
• 使用 Lakeflow Jobs 实现管道自动化。
•（附加内容）使用 Spark Declarative Pipelines 构建声明式管道。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29385","entityUrl":{"path":"/training/catalog/building-persistent-memory-for-ai-agents-with-lakebase-on-databricks-5706"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-persistent-memory-for-ai-agents-with-lakebase-on-databricks-5706"}}],"nid":29385,"vid":231472,"title":"Building Persistent Memory for AI Agents with Lakebase on Databricks","price":"0.00","duration":14400,"body":{"processed":"This course teaches how to build AI agents that remember — both within a conversation and across sessions — using Databricks Lakebase as the persistence backend. Students learn how LangGraph’s Checkpointer system provides short-term memory (within-session conversation continuity) and how LangGraph’s Store provides long-term memory (cross-session user preferences), both backed by Lakebase Autoscaling. Students build and test these memory systems in notebooks, observe agent behavior through MLflow traces, and deploy a fully stateful agent as a Databricks App.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"29386","entityUrl":{"path":"/training/catalog/building-persistent-memory-for-ai-agents-with-lakebase-on-databricks-5707"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-persistent-memory-for-ai-agents-with-lakebase-on-databricks-5707"}}],"nid":29386,"vid":231473,"title":"Building Persistent Memory for AI Agents with Lakebase on Databricks","price":"75.00","duration":14400,"body":{"processed":"This course teaches how to build AI agents that remember — both within a conversation and across sessions — using Databricks Lakebase as the persistence backend. Students learn how LangGraph’s Checkpointer system provides short-term memory (within-session conversation continuity) and how LangGraph’s Store provides long-term memory (cross-session user preferences), both backed by Lakebase Autoscaling. Students build and test these memory systems in notebooks, observe agent behavior through MLflow traces, and deploy a fully stateful agent as a Databricks App.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"29374","entityUrl":{"path":"/training/catalog/vibe-coding-a-databricks-app-5679"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/vibe-coding-a-databricks-app-5679"}}],"nid":29374,"vid":231324,"title":"Vibe Coding a Databricks App","price":"75.00","duration":7200,"body":{"processed":"This is a hands-on course that shows learners how AI-assisted development can accelerate the journey from an idea to a functional application. Participants use Databricks Genie Code to turn plain-language ideas into a working Databricks App, then iteratively refine the app by identifying issues, improving prompts, and applying production-oriented best practices.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29375","entityUrl":{"path":"/training/catalog/context-is-everything-lakebase-agent-memory-5680"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/context-is-everything-lakebase-agent-memory-5680"}}],"nid":29375,"vid":231325,"title":"Context Is Everything: Lakebase Agent Memory","price":"75.00","duration":7200,"body":{"processed":"Build a complete, stateful LangGraph agent and deploy it as a Databricks App. You'll create an assistant that answers business questions by calling Unity Catalog function tools over live data, sustains multi-turn conversations through short-term checkpointed state, and recalls each user across sessions days apart via persistent long-term memory. Along the way you'll see why context is everything: an agent is only as good as the context assembled into its prompt, and memory — backed by Lakebase Postgres — is how that context survives beyond a single inference.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29373","entityUrl":{"path":"/training/catalog/no-code-etl-with-lakeflow-designer-5642"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/no-code-etl-with-lakeflow-designer-5642"}}],"nid":29373,"vid":231272,"title":"No Code ETL with Lakeflow Designer","price":"75.00","duration":7200,"body":{"processed":"No-Code ETL with Lakeflow Designer shows how to build a complete medallion ETL workflow, from bronze to silver to gold, visually and without writing pipeline code. You will use Databricks Lakeflow Designer and its built-in AI authoring assistant, Genie Code.
In Lakeflow Designer, you build workflows on a visual canvas using operators. Operators are the building blocks of a data pipeline, with each operator performing an action such as adding a source, filtering or transforming data, aggregating data, joining datasets, or creating an output table.
Throughout the course, you will build workflows in two ways:
• Add and configure operators using the point-and-click interface.
• Describe transformations in natural language and use Genie Code to generate operators and workflows.
Using a realistic meeting and session dataset that includes sessions, participants, and feedback, the course introduces the medallion architecture in Unity Catalog and shows how to add bronze sources to the canvas, clean and reshape data into silver tables, and aggregate and join data into analytics-ready gold tables.
You will also learn how to schedule the workflow and deliver insights to business users through an AI/BI dashboard, a Genie Agent (Space), and Genie One. An optional bonus topic extends the workflow with the AI Function operator to derive sentiment from free-form feedback.
By the end of the course, you will understand how raw data moves through a governed and scheduled medallion architecture to produce analytics-ready gold tables and consumer-ready insights using a visual, AI-assisted experience on the Databricks Lakehouse.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29330","entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-4620"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-4620"}}],"nid":29330,"vid":230466,"title":"Building Enterprise Applications with Databricks Apps","price":"0.00","duration":7200,"body":{"processed":"This course introduces Databricks Apps, a new feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.
The course begins with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29331","entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-4621"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-enterprise-applications-with-databricks-apps-4621"}}],"nid":29331,"vid":230467,"title":"Building Enterprise Applications with Databricks Apps","price":"75.00","duration":10800,"body":{"processed":"This course introduces Databricks Apps, a new feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.
The course begins with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29281","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-mandarin-chinese-5577"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-machine-learning-mandarin-chinese-5577"}}],"nid":29281,"vid":229707,"title":"Get Started with Databricks for Machine Learning - Mandarin Chinese","price":"75.00","duration":10800,"body":{"processed":"在本课程中，您将培养使用 Databricks Data Intelligence Platform 执行机器学习工作流并支持数据科学工作负载所需的基础技能。您将从机器学习从业者的视角探索该平台，内容涵盖使用 Mosaic AI Feature Engineering 构建和管理特征、使用 MLflow 进行端到端模型生命周期管理，以及使用 Lakeflow Jobs 进行管道编排等主题。此外，您还将学习如何使用 Databricks AI Model Serving 进行实时模型推理，并通过 Genie Code - Data Science Agent Mode 体验 Databricks 透明、对话式的模型开发方式——在其中，您可以使用自然语言提示，直接在笔记本中生成、运行并迭代优化可执行的 ML 工作流。本课程包含由讲师主导的演示，并以一个全面的实验作为收尾，巩固贯穿全程所讲解的概念。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29080","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-2469"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-2469"}}],"nid":29080,"vid":228201,"title":"Get Started with Databricks for Data Engineering","price":"0.00","duration":7200,"body":{"processed":"This course introduces the foundational skills needed to perform a basic data engineering workflow on the Databricks Data Intelligence Platform. You will explore the workspace, work with Unity Catalog, and learn the day-to-day building blocks a data engineer uses on Databricks.
The course follows a hands-on path. You start by getting oriented in the workspace, then work through paired Demo and Lab notebooks for each topic. Demos walk you through a concept with the instructor or a guided notebook.
The content covers:
• The Databricks Data Intelligence Platform and how the Databricks workspace, Unity Catalog, and notebooks fit together.
• Creating and managing Delta Lake tables.
• Modifying data with INSERT, UPDATE, and DELETE.
• Exploring version history and time travel on UC tables.
• Ingesting data with Lakeflow Connect options: CTAS, the Upload UI, and COPY INTO.
• Building a Medallion Architecture pipeline that transforms data through Bronze, Silver, and Gold layers.
• Automating pipelines with Lakeflow Jobs.
• (Bonus) Building a declarative pipeline with Apache Spark™ Declarative Pipelines.
By the end of the course, you will be comfortable creating Delta Lake tables, ingesting data into them, transforming that data through a Medallion pipeline, and automating the whole thing as a scheduled job.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29081","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-2521"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-2521"}}],"nid":29081,"vid":228202,"title":"Get Started with Databricks for Data Engineering","price":"75.00","duration":10800,"body":{"processed":"This course introduces the foundational skills needed to perform a basic data engineering workflow on the Databricks Data Intelligence Platform. You will explore the workspace, work with Unity Catalog, and learn the day-to-day building blocks a data engineer uses on Databricks.
The course follows a hands-on path. You start by getting oriented in the workspace, then work through paired Demo and Lab notebooks for each topic. Demos walk you through a concept with the instructor or a guided notebook.
The content covers:
• The Databricks Data Intelligence Platform and how the Databricks workspace, Unity Catalog, and notebooks fit together.
• Creating and managing Delta Lake tables.
• Modifying data with INSERT, UPDATE, and DELETE.
• Exploring version history and time travel on UC tables.
• Ingesting data with Lakeflow Connect options: CTAS, the Upload UI, and COPY INTO.
• Building a Medallion Architecture pipeline that transforms data through Bronze, Silver, and Gold layers.
• Automating pipelines with Lakeflow Jobs.
• (Bonus) Building a declarative pipeline with Apache Spark™ Declarative Pipelines.
By the end of the course, you will be comfortable creating Delta Lake tables, ingesting data into them, transforming that data through a Medallion pipeline, and automating the whole thing as a scheduled job.
This course teaches data analysts how to design, build, publish, and operate AI/BI Dashboards in Databricks. AI/BI Dashboards combine governed Unity Catalog data with interactive visualizations, filters, and Genie integration so business users can explore answers without writing code.
The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.
The content covers:
• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.
• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.
• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.
• Using Genie Code to draft SQL, charts, and filters from natural language prompts.
• Adding filters to make dashboards interactive and responsive to viewer questions.
• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.
• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
This course teaches data analysts how to design, build, publish, and operate AI/BI Dashboards in Databricks. AI/BI Dashboards combine governed Unity Catalog data with interactive visualizations, filters, and Genie integration so business users can explore answers without writing code.
The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.
The content covers:
• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.
• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.
• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.
• Using Genie Code to draft SQL, charts, and filters from natural language prompts.
• Adding filters to make dashboards interactive and responsive to viewer questions.
• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.
• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29009","entityUrl":{"path":"/training/catalog/get-started-with-ai-agents-on-databricks-mandarin-chinese-5482"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-ai-agents-on-databricks-mandarin-chinese-5482"}}],"nid":29009,"vid":227332,"title":"Get Started with AI Agents on Databricks - Mandarin Chinese","price":"0.00","duration":7200,"body":{"processed":"本课程是 AI Agent 的入门介绍，内容涵盖 AI Agent 在现代 AI 应用中的作用，以及如何在 Databricks 平台上构建 AI Agent 应用。您将学习 AI Agent 的基本原理、其与传统 AI 系统的区别，并深入了解其关键组成部分。通过交互式演示和实操实验，您将了解如何在 Databricks 上使用 Mosaic AI 与 Agent Bricks 构建、部署并评估 AI Agent。完成本课程后，您将掌握如何使用 Databricks Data Intelligence Platform 创建并部署 AI Agent。
In this course, you will learn how to design, implement, and govern catalog structures and large-scale data organization on the Databricks Data Intelligence Platform. It offers a comprehensive view of Unity Catalog as the centralized governance layer for an enterprise lakehouse. Divided into five modules, it begins by placing Unity Catalog within the cloud deployment model — covering the Account Console, metastore creation, and the administrator role hierarchy. You will then translate organizational topology (business units, regions, and dev/QA/prod environments) into a scalable catalog and schema design using naming conventions, ownership patterns, and MANAGE delegation. The course then covers secure storage integration with storage credentials, external locations, the managed-storage hierarchy, managed versus external tables, and UC Volumes for non-tabular data. Next, you will apply access patterns and isolation strategies — the three-level GRANT chain, workspace-catalog binding, and schema-level Attribute-Based Access Control (ABAC) policies — to enforce fine-grained data protection at scale. Finally, the course closes with best practices for catalog design, automation, least-privilege permissions, and group-based access management.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28956","entityUrl":{"path":"/training/catalog/catalog-management-and-data-organization-5458"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/catalog-management-and-data-organization-5458"}}],"nid":28956,"vid":226437,"title":"Catalog Management and Data Organization","price":"0.00","duration":7200,"body":{"processed":"In this course, you will learn how to design, implement, and govern catalog structures and large-scale data organization on the Databricks Data Intelligence Platform. It offers a comprehensive view of Unity Catalog as the centralized governance layer for an enterprise lakehouse. Divided into five modules, it begins by placing Unity Catalog within the cloud deployment model — covering the Account Console, metastore creation, and the administrator role hierarchy. You will then translate organizational topology (business units, regions, and dev/QA/prod environments) into a scalable catalog and schema design using naming conventions, ownership patterns, and MANAGE delegation. The course then covers secure storage integration with storage credentials, external locations, the managed-storage hierarchy, managed versus external tables, and UC Volumes for non-tabular data. Next, you will apply access patterns and isolation strategies — the three-level GRANT chain, workspace-catalog binding, and schema-level Attribute-Based Access Control (ABAC) policies — to enforce fine-grained data protection at scale. Finally, the course closes with best practices for catalog design, automation, least-privilege permissions, and group-based access management.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28804","entityUrl":{"path":"/training/catalog/data-modeling-strategies-3742"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-modeling-strategies-3742"}}],"nid":28804,"vid":224966,"title":"Data Modeling Strategies","price":"0.00","duration":7200,"body":{"processed":"This course walks practitioners through the full spectrum of data modelling approaches on the Databricks Data Intelligence Platform - from classical data warehouse techniques (Inmon, Kimball, Data Vault 2.0), through Feature Store-driven ML use cases, to productising data via Data Products on Unity Catalog.
Each modelling approach is introduced with a lecture, then reinforced with a hands-on demo against a shared dataset (TPC-H samples). The course finishes with a comprehensive end-to-end lab that exercises ERM, dimensional modelling, Data Vault 2.0, and the Feature Store in a single integrated workflow.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28802","entityUrl":{"path":"/training/catalog/data-modeling-strategies-3737"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-modeling-strategies-3737"}}],"nid":28802,"vid":224961,"title":"Data Modeling Strategies","price":"75.00","duration":10800,"body":{"processed":"This course walks practitioners through the full spectrum of data modelling approaches on the Databricks Data Intelligence Platform - from classical data warehouse techniques (Inmon, Kimball, Data Vault 2.0), through Feature Store-driven ML use cases, to productising data via Data Products on Unity Catalog.
Each modelling approach is introduced with a lecture, then reinforced with a hands-on demo against a shared dataset (TPC-H samples). The course finishes with a comprehensive end-to-end lab that exercises ERM, dimensional modelling, Data Vault 2.0, and the Feature Store in a single integrated workflow.
Note:
1. The course includes practice labs that the learners should perform after going through the entire course.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28769","entityUrl":{"path":"/training/catalog/data-interoperability-with-unity-catalog-4556"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-interoperability-with-unity-catalog-4556"}}],"nid":28769,"vid":224742,"title":"Data Interoperability with Unity Catalog","price":"0.00","duration":7200,"body":{"processed":"This course explores how to achieve data interoperability between systems using Databricks Unity Catalog as a unified governance layer, using both Delta and Iceberg open table formats. Participants will learn to implement, manage and optimize a data environment where tables can be accessed by both Delta and Iceberg clients, enabling cross-platform analytics and eliminating data silos.
This course is designed for Data Engineers, Platform Administrators, and Analytics Engineers responsible for implementing and managing multi-format data architectures. You will gain the skills to use Unity Catalog for unified governance across Delta and Iceberg table formats and across federated external systems.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"28770","entityUrl":{"path":"/training/catalog/data-interoperability-with-unity-catalog-4557"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-interoperability-with-unity-catalog-4557"}}],"nid":28770,"vid":224743,"title":"Data Interoperability with Unity Catalog","price":"75.00","duration":10800,"body":{"processed":"This course explores how to achieve data interoperability between systems using Databricks Unity Catalog as a unified governance layer, using both Delta and Iceberg open table formats. Participants will learn to implement, manage and optimize a data environment where tables can be accessed by both Delta and Iceberg clients, enabling cross-platform analytics and eliminating data silos.
This course is designed for Data Engineers, Platform Administrators, and Analytics Engineers responsible for implementing and managing multi-format data architectures. You will gain the skills to use Unity Catalog for unified governance across Delta and Iceberg table formats and across federated external systems.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"28755","entityUrl":{"path":"/training/catalog/architecting-data-warehouses-for-large-scale-deployments-5401"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/architecting-data-warehouses-for-large-scale-deployments-5401"}}],"nid":28755,"vid":223388,"title":"Architecting Data Warehouses for Large-Scale Deployments","price":"0.00","duration":7200,"body":{"processed":"This course covers performance optimization, cost control, and security for large-scale data warehousing deployments.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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This course introduces Databricks Genie One, an AI-powered cowork environment designed around your needs and work, where you can ask questions in plain language about your organization's data and get governed, secure answers, schedule reports to run automatically, and automate your workflow to get more work done faster and more accurately, as it's based on your data and business. You'll learn what Genie, Genie One, and Genie Agents are, how they all keep your data secure, and the best practices for getting the best results.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28307","entityUrl":{"path":"/training/catalog/databricks-performance-optimization-2967"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-performance-optimization-2967"}}],"nid":28307,"vid":217612,"title":"Databricks Performance Optimization","price":"0.00","duration":7200,"body":{"processed":"In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.
Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is part of the 'Advanced Data Engineering with Databricks' course series.
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You will learn how to apply modularity principles in PySpark to create reusable components and structure code efficiently. Hands-on experience includes designing and implementing unit tests for PySpark functions using the pytest framework, followed by integration testing for Databricks data pipelines with Spark Declarative Pipeline and Jobs to ensure reliability.
The course also covers essential Git operations within Databricks, including using Databricks Git Folders to integrate continuous integration practices. Finally, you will take a high level look at various deployment methods for Databricks assets, such as REST API, CLI, SDK, and Declarative Automation Bundles (DABs), providing you with the knowledge of techniques to deploy and manage your pipelines.
By the end of the course, you will be proficient in software engineering and DevOps best practices, enabling you to build scalable, maintainable, and efficient data engineering solutions.
Note:
1. This is the fourth course in the 'Data Engineering with Databricks' series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
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• You will learn to design and implement data workloads using Directed Acyclic Graphs (DAGs), configure various scheduling options, and implement advanced workflow features such as conditional task execution, run-if dependencies, and for each loops.
• The course covers best practices for creating robust, production-ready pipelines with proper compute selection, modular orchestration, error handling techniques, and fault-tolerant design-all natively integrated within the Databricks Data Intelligence Platform.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28486","entityUrl":{"path":"/training/catalog/machine-learning-model-development-2393"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-model-development-2393"}}],"nid":28486,"vid":217791,"title":"Machine Learning Model Development","price":"750.00","duration":14400,"body":{"processed":"This comprehensive course provides a practical guide to developing traditional machine learning models on Databricks, emphasizing hands-on demonstrations and workflows using popular ML libraries. Participants will explore key ML techniques, including regression and clustering, while leveraging Databricks' powerful capabilities. The course covers MLflow integration for model tracking, Databricks Feature Store for feature management, and Optuna for hyperparameter tuning. Additionally, participants will learn how to accelerate model development with Genie Code, Databricks' AI-powered coding assistant that uses natural language, MCP connections, instructions, and skills to guide the full ML lifecycle. By the end of the course, learners will have real-world, practical skills to develop, optimize, and deploy machine learning models efficiently in the Databricks environment.
Languages Available: English | 日本語 | Português BR | 한국어
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Topics covered include:
• Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
• How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
• Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.
The content covers:
• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.
• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.
• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.
• Using Genie Code to draft SQL, charts, and filters from natural language prompts.
• Adding filters to make dashboards interactive and responsive to viewer questions.
• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.
• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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Languages Available: English | 日本語 | Português BR | 한국어
This course is designed to introduce three primary machine learning deployment strategies and illustrate the implementation of each strategy on Databricks. Following an exploration of the fundamentals of model deployment, the course delves into batch inference, offering hands-on demonstrations and labs for utilizing a model in batch inference scenarios, along with considerations for performance optimization. The second part of the course comprehensively covers pipeline deployment, while the final segment focuses on real-time deployment. Participants will engage in hands-on demonstrations and labs, deploying models with Model Serving and utilizing the serving endpoint for real-time inference.
Note:
1. This is the third course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Throughout the course, you will dive into modern data ingestion and processing techniques, mastering tools like Liquid Clustering for layout optimization and the Multiplex Streaming pattern for mixed-schema events. By the end of the modules, you will know how to confidently handle schema evolution, automate Change Data Capture (CDC), and ensure data integrity.
Through lectures and hands-on demos, you will:
• Build multi-flow pipelines to ingest multi-source data into a unified Bronze table.
• Apply Liquid Clustering and Data Quality Expectations across Silver and Gold layers.
• Implement the Multiplex pattern with Iceberg UniForm for cross-platform data access.
• Automate SCD Type 2 history tracking using AUTO CDC INTO.
• Design zero-data-loss quarantine pipelines to audit and manage invalid records.
Note:
1. This course is the first in the 'Advanced Data Engineering with Databricks' series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Additionally, you’ll be guided through trial management and upgrade options, ensuring you can effectively transition from trial to paid accounts. The course also includes an internal-only module on the evolution of trial credits and account activation methods. By the end of the course, you will have a solid foundation in using Databricks Express Setup for data and AI workloads, enabling you to confidently explore and analyze data, collaborate with peers, and manage your Databricks environment efficiently.
Note: Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28454","entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-1511"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/get-started-with-databricks-for-data-engineering-1511"}}],"nid":28454,"vid":217759,"title":"Get Started with Databricks for Data Engineering","price":"0.00","duration":7200,"body":{"processed":"This course introduces the foundational skills needed to perform a basic data engineering workflow on the Databricks Data Intelligence Platform. You will explore the workspace, work with Unity Catalog, and learn the day-to-day building blocks a data engineer uses on Databricks.
The course follows a hands-on path. You start by getting oriented in the workspace, then work through paired Demo and Lab notebooks for each topic. Demos walk you through a concept with the instructor or a guided notebook.
The content covers:
• The Databricks Data Intelligence Platform and how the Databricks workspace, Unity Catalog, and notebooks fit together.
• Creating and managing Delta Lake tables.
• Modifying data with INSERT, UPDATE, and DELETE.
• Exploring version history and time travel on UC tables.
• Ingesting data with Lakeflow Connect options: CTAS, the Upload UI, and COPY INTO.
• Building a Medallion Architecture pipeline that transforms data through Bronze, Silver, and Gold layers.
• Automating pipelines with Lakeflow Jobs.
• (Bonus) Building a declarative pipeline with Apache Spark™ Declarative Pipelines.
By the end of the course, you will be comfortable creating Delta Lake tables, ingesting data into them, transforming that data through a Medallion pipeline, and automating the whole thing as a scheduled job.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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Note:
1. This is the third course in the 'Machine Learning with Databricks’ series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.
You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.
This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.
By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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• Apply Liquid Clustering and Data Quality Expectations across Silver and Gold layers.
• Implement the Multiplex pattern with Iceberg UniForm for cross-platform data access.
• Automate SCD Type 2 history tracking using AUTO CDC INTO.
• Design zero-data-loss quarantine pipelines to audit and manage invalid records.
Note:
1. This course is the first in the 'Advanced Data Engineering with Databricks' series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.
Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어
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• Run notebooks in both Python and SQL
• Format notebook content using basic Markdown
02: Get Started with Databricks Free Edition
• Explore Unity Catalog objects (catalogs, schemas, tables, volumes)
• Upload a local file into a Volume
• Access and use data from Databricks Marketplace
• Ingest and visualize data within a notebook
• Get a high-level tour of the SQL Editor and dashboards
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You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.
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• Query Lakebase data from Databricks using Lakehouse Federation and foreign catalogs
• Perform Reverse ETL by synchronizing Delta tables to Lakebase
• Connect to Lakebase from Python and perform basic CRUD operations
This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.
By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.
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Each modelling approach is introduced with a lecture, then reinforced with a hands-on demo against a shared dataset (TPC-H samples). The course finishes with a comprehensive end-to-end lab that exercises ERM, dimensional modelling, Data Vault 2.0, and the Feature Store in a single integrated workflow.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어
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You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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Languages Available: English | 日本語 | Português BR | 한국어
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is the second in the 'Advanced Data Engineering with Databricks' series.
Languages Available: Languages Available: English | 日本語 | Português BR | 한국어
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• You will learn to design and implement data workloads using Directed Acyclic Graphs (DAGs), configure various scheduling options, and implement advanced workflow features such as conditional task execution, run-if dependencies, and for each loops.
• The course covers best practices for creating robust, production-ready pipelines with proper compute selection, modular orchestration, error handling techniques, and fault-tolerant design-all natively integrated within the Databricks Data Intelligence Platform.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-02T09:00:00"},"endDate":{"value":"2026-10-02T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-10-02T13:00:00"},"endDate":{"value":"2026-10-02T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-10-06T09:00:00"},"endDate":{"value":"2026-10-06T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-11-04T13:00:00"},"endDate":{"value":"2026-11-04T17:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2026-11-04T09:00:00"},"endDate":{"value":"2026-11-04T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-11-04T09:00:00"},"endDate":{"value":"2026-11-04T13:00:00"},"timezone":"America/Los_Angeles"}},{"entity":{"startDate":{"value":"2026-12-02T09:00:00"},"endDate":{"value":"2026-12-02T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-12-02T13:00:00"},"endDate":{"value":"2026-12-02T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-12-02T09:00:00"},"endDate":{"value":"2026-12-02T13:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-06T09:00:00"},"endDate":{"value":"2027-01-06T13:00:00"},"timezone":"Asia/Singapore"}},{"entity":{"startDate":{"value":"2027-01-06T13:00:00"},"endDate":{"value":"2027-01-06T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-07T09:00:00"},"endDate":{"value":"2027-01-07T13:00:00"},"timezone":"Europe/Paris"}}]},{"id":"28493","entityUrl":{"path":"/training/catalog/machine-learning-with-databricks-2422"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-with-databricks-2422"}}],"nid":28493,"vid":217798,"title":"Machine Learning with Databricks","price":"1500.00","duration":57600,"body":{"processed":"Welcome to Machine Learning with Databricks!
This course is your gateway to mastering machine learning workflows on Databricks. Dive into data preparation, model development, deployment, and operations, guided by expert instructors. Learn essential skills for data exploration, model training, and deployment strategies tailored for Databricks. By course end, you'll have the knowledge and confidence to navigate the entire machine learning lifecycle on the Databricks platform, empowering you to build and deploy robust machine learning solutions efficiently.
Note: the Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Data Preparation for Machine Learning
This course focuses on the fundamentals of preparing data for machine learning using Databricks. Participants will learn essential skills for exploring, cleaning, and organizing data tailored for traditional machine learning applications. Key topics include data visualization, feature engineering, and optimal feature storage strategies. Through practical exercises, participants will gain hands-on experience in efficiently preparing data sets for machine learning within the Databricks. This course is designed for associate-level data scientists and machine learning practitioners. and individuals seeking to enhance their proficiency in data preparation, ensuring a solid foundation for successful machine learning model deployment.
Machine Learning Model Development
This comprehensive course provides a practical guide to developing traditional machine learning models on Databricks, emphasizing hands-on demonstrations and workflows using popular ML libraries. Participants will explore key ML techniques, including regression and clustering, while leveraging Databricks' powerful capabilities. The course covers MLflow integration for model tracking, Databricks Feature Store for feature management, and Optuna for hyperparameter tuning. Additionally, participants will learn how to accelerate model development with Genie Code, Databricks' AI-powered coding assistant that uses natural language, MCP connections, instructions, and skills to guide the full ML lifecycle. By the end of the course, learners will have real-world, practical skills to develop, optimize, and deploy machine learning models efficiently in the Databricks environment.
Machine Learning Model Deployment
This course is designed to introduce three primary machine learning deployment strategies and illustrate the implementation of each strategy on Databricks. Following an exploration of the fundamentals of model deployment, the course delves into batch inference, offering hands-on demonstrations and labs for utilizing a model in batch inference scenarios, along with considerations for performance optimization. The second part of the course comprehensively covers pipeline deployment, while the final segment focuses on real-time deployment. Participants will engage in hands-on demonstrations and labs, deploying models with Model Serving and utilizing the serving endpoint for real-time inference.
Machine Learning Operations
This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.
Languages Available: English | 日本語 | Português BR | 한국어
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is the second in the 'Advanced Data Engineering with Databricks' series.
Languages Available: Languages Available: English | 日本語 | Português BR | 한국어
This course introduces users to the essential concepts and skills needed to build data pipelines using Apache Spark™ Declarative Pipelines (SDP) in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Spark Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.
Topics covered include:
• Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
• How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
• Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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The course begins with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28361","entityUrl":{"path":"/training/catalog/machine-learning-at-scale-3412"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-at-scale-3412"}}],"nid":28361,"vid":217666,"title":"Machine Learning at Scale","price":"75.00","duration":10800,"body":{"processed":"In this course, you will gain theoretical and practical knowledge of Apache Spark’s architecture and its application to machine learning workloads within Databricks. You will learn when to use Spark for data preparation, model training, and deployment, while also gaining hands-on experience with Spark ML and pandas APIs on Spark. This course will introduce you to advanced concepts like hyperparameter tuning and scaling Optuna with Spark. This course will use features and concepts introduced in the associate course such as MLflow and Unity Catalog for comprehensive model packaging and governance.
Note:
1. This course is the first in the series of Advanced Machine Learning.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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Languages Available: English | 日本語 | 한국어
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After successfully completing this assessment, you will be awarded an AWS Databricks Platform Architect badge.
This course introduces the SAP Databricks connector and its strategic value within the SAP Databricks partnership. Participants will explore how Delta Sharing enables zero-copy collaboration across platforms while examining both curated and custom offerings that integrate with SAP architectures. By course completion, students will be equipped to establish connections and facilitate seamless information flow from SAP Business Data Cloud to Databricks environments.
Analytics Fundamentals is a one-hour, introductory course that orients practitioners to modern analytics on the Databricks Data Intelligence Platform. This course covers the five pillars of modern analytics: lakehouse architecture, data transformation with an expanded focus on SQL-based ETL using Databricks SQL, unified semantics, AI-powered dashboards, and conversational analytics with Genie.
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Note:
1. This course is the first in the series of Advanced Machine Learning.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
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You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.
Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어
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In this course, you will explore Unity Catalog and fine-grained access controls on Databricks with hands-on demos and a capstone lab. You will learn about table types, catalog and schema configuration, group-based access management, and access control migration strategies. The course includes demos on applying Fine-Grained Access Controls with Row Level Security and Column Masking, Attribute based access control, combining controls, migrating controls, and a lab for comprehensive governance implementation.
You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
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You will learn how Genie Agents fit into the Databricks AI/BI product family and how they translate natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Agent that delivers accurate, consistent, and trustworthy results.
You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Agent using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.
You will also learn how to share Genie Agents with business users through Genie One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.
By the end of the course, you will be able to create and manage a production-ready Genie Agent that delivers governed, self-service conversational analytics at scale.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Below, we describe each of the four, four-hour modules included in this course.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Introduction to Apache Spark
This beginner-friendly course covers the fundamentals of Apache Spark for large-scale data processing. You will explore Spark’s distributed architecture, master the DataFrame API, and learn to read, write, and process data using Python. Through hands-on exercises, you will build the skills needed to execute Spark transformations and actions efficiently.
Developing Applications with Apache Spark
Master scalable data processing with Apache Spark in this course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.
Stream Processing and Analysis with Apache Spark
This course guides learners on how to develop scalable, fault-tolerant stream processing applications using the Spark Structured Streaming API on Databricks.
Monitoring and Optimizing Apache Spark Workloads on Databricks
This course covers core Databricks platform components and Apache Spark with Delta Lake, focusing on the Lakehouse architecture, Unity Catalog, and data management techniques like ACID transactions and table maintenance. Additionally, it teaches students how to optimize query performance through partitioning, shuffles, and tuning tools, while utilizing the Spark UI to monitor applications and resolve bottlenecks.
Languages Available: English | 日本語 | 한국어
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Next, you’ll develop practical skills for ingesting data from cloud object storage using Lakeflow Connect Standard Connectors. This includes working with methods such as CREATE TABLE AS SELECT (CTAS), COPY INTO, and Auto Loader, with an emphasis on the benefits and considerations of each approach. You’ll also learn how to append metadata columns to your bronze-level tables during ingestion into the Databricks Data Intelligence Platform. The course then covers how to handle records that don’t match your table schema using the rescued data column, along with strategies for managing and analyzing this data. You’ll also explore techniques for ingesting and flattening semi-structured JSON data.
Following this, you’ll explore how to perform enterprise-grade data ingestion using Lakeflow Connect Managed Connectors to bring in data from databases and Software-as-a-Service (SaaS) applications. The course also introduces Partner Connect as an option for integrating partner tools into your ingestion workloads.
Finally, the course wraps up with alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with a strong foundation to support modern data engineering use cases.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28242","entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-5220"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-5220"}}],"nid":28242,"vid":217547,"title":"Building Reliable Conversational Agents with Genie","price":"75.00","duration":10800,"body":{"processed":"This course teaches you how to design, build, and maintain a Databricks Genie Agent, a natural language interface that enables business users to ask questions about governed data and receive SQL-backed answers without writing code.
You will learn how Genie Agents fit into the Databricks AI/BI product family and how they translate natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Agent that delivers accurate, consistent, and trustworthy results.
You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Agent using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.
You will also learn how to share Genie Agents with business users through Genie One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.
By the end of the course, you will be able to create and manage a production-ready Genie Agent that delivers governed, self-service conversational analytics at scale.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28377","entityUrl":{"path":"/training/catalog/advanced-machine-learning-with-databricks-3486"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/advanced-machine-learning-with-databricks-3486"}}],"nid":28377,"vid":217682,"title":"Advanced Machine Learning with Databricks","price":"1000.00","duration":28800,"body":{"processed":"This course is aimed at data scientists and machine learning practitioners and consists of two, four-hours modules.
Machine Learning at Scale
In this course, you will gain theoretical and practical knowledge of Apache Spark’s architecture and its application to machine learning workloads within Databricks. You will learn when to use Spark for data preparation, model training, and deployment, while also gaining hands-on experience with Spark ML and pandas APIs on Spark. This course will introduce you to advanced concepts like hyperparameter tuning and scaling Optuna with Spark. This course will use features and concepts introduced in the associate course such as MLflow and Unity Catalog for comprehensive model packaging and governance.
Advanced Machine Learning Operations
In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Declarative Automation Bundles (DABs), Lakeflow Jobs, and Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-14T10:00:00"},"endDate":{"value":"2026-10-15T14:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-10-28T13:00:00"},"endDate":{"value":"2026-10-29T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-11-03T10:00:00"},"endDate":{"value":"2026-11-03T18:00:00"},"timezone":"Asia/Singapore"}},{"entity":{"startDate":{"value":"2026-11-03T09:00:00"},"endDate":{"value":"2026-11-03T17:00:00"},"timezone":"Europe/London"}},{"entity":{"startDate":{"value":"2026-11-03T09:00:00"},"endDate":{"value":"2026-11-03T17:00:00"},"timezone":"America/Los_Angeles"}}]},{"id":"28445","entityUrl":{"path":"/training/catalog/data-analysis-with-databricks-830"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-analysis-with-databricks-830"}}],"nid":28445,"vid":217750,"title":"Data Analysis with Databricks","price":"1000.00","duration":28800,"body":{"processed":"This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.
This course consists of two four-hour modules.
Note: the Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
SQL Analytics on Databricks
In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights.
You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.
Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.
AI/BI for Data Analysts
This course teaches data analysts how to design, build, publish, and operate AI/BI Dashboards in Databricks. AI/BI Dashboards combine governed Unity Catalog data with interactive visualizations, filters, and Genie integration so business users can explore answers without writing code.
The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.
The content covers:
• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.
• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.
• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.
• Using Genie Code to draft SQL, charts, and filters from natural language prompts.
• Adding filters to make dashboards interactive and responsive to viewer questions.
• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.
• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
\n\n \n
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Note: This course is part of the 'Advanced Data Engineering with Databricks' course series.
Languages Available: English | 日本語 | Português BR | 한국어
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"28243","entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-5222"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-reliable-conversational-agents-with-genie-5222"}}],"nid":28243,"vid":217548,"title":"Building Reliable Conversational Agents with Genie","price":"0.00","duration":7200,"body":{"processed":"This course teaches you how to design, build, and maintain a Databricks Genie Agent, a natural language interface that enables business users to ask questions about governed data and receive SQL-backed answers without writing code.
You will learn how Genie Agents fit into the Databricks AI/BI product family and how they translate natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Agent that delivers accurate, consistent, and trustworthy results.
You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Agent using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.
You will also learn how to share Genie Agents with business users through Genie One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.
By the end of the course, you will be able to create and manage a production-ready Genie Agent that delivers governed, self-service conversational analytics at scale.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28379","entityUrl":{"path":"/training/catalog/databricks-data-privacy-3490"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-data-privacy-3490"}}],"nid":28379,"vid":217684,"title":"Databricks Data Privacy","price":"750.00","duration":14400,"body":{"processed":"This content provides a comprehensive guide to managing data privacy within Databricks. It covers key topics like Delta Lake architecture, regional data isolation, GDPR/CCPA compliance, and Change Data Feed (CDF) usage. Through practical demos and hands-on labs, participants learn to use Unity Catalog features for securing sensitive data and ensuring compliance, empowering them to safeguard data integrity effectively.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-14T09:00:00"},"endDate":{"value":"2026-10-14T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-10-14T09:00:00"},"endDate":{"value":"2026-10-14T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-10-14T13:00:00"},"endDate":{"value":"2026-10-14T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-11-18T13:00:00"},"endDate":{"value":"2026-11-18T17:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"America/Los_Angeles"}},{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-12-09T13:00:00"},"endDate":{"value":"2026-12-09T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2027-01-20T09:00:00"},"endDate":{"value":"2027-01-20T13:00:00"},"timezone":"Asia/Singapore"}},{"entity":{"startDate":{"value":"2027-01-20T09:00:00"},"endDate":{"value":"2027-01-20T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2027-01-20T13:00:00"},"endDate":{"value":"2027-01-20T17:00:00"},"timezone":"America/New_York"}}]},{"id":"28446","entityUrl":{"path":"/training/catalog/data-engineering-with-databricks-911"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/data-engineering-with-databricks-911"}}],"nid":28446,"vid":217751,"title":"Data Engineering with Databricks","price":"1500.00","duration":57600,"body":{"processed":"This is an introductory course that serves as an appropriate entry point to learn Data Engineering with Databricks.
Below, we describe each of the four, four-hour modules included in this course.
Note: For the following four modules, the Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
1. Data Ingestion with Lakeflow Connect
This course provides a comprehensive introduction to Lakeflow Connect, a scalable and simplified solution for ingesting data into Databricks from a wide range of sources. You’ll begin by exploring the different types of Lakeflow Connect connectors (Standard and Managed) and learn various data ingestion techniques, including batch, incremental batch, and streaming ingestion. You'll also review the key benefits of using Delta table and the Medallion architecture
Next, you’ll develop practical skills for ingesting data from cloud object storage using Lakeflow Connect Standard Connectors. This includes working with methods such as CREATE TABLE AS SELECT (CTAS), COPY INTO, and Auto Loader, with an emphasis on the benefits and considerations of each approach. You’ll also learn how to append metadata columns to your bronze-level tables during ingestion into the Databricks Data Intelligence Platform. The course then covers how to handle records that don’t match your table schema using the rescued data column, along with strategies for managing and analyzing this data. You’ll also explore techniques for ingesting and flattening semi-structured JSON data.
Following this, you’ll explore how to perform enterprise-grade data ingestion using Lakeflow Connect Managed Connectors to bring in data from databases and Software-as-a-Service (SaaS) applications. The course also introduces Partner Connect as an option for integrating partner tools into your ingestion workloads.
Finally, the course wraps up with alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with a strong foundation to support modern data engineering use cases.
2. Deploy Workloads with Lakeflow Jobs
Deploy Workloads with Lakeflow Jobs course teaches how to orchestrate and automate data, analytics, and AI workflows using Lakeflow Jobs as a unified orchestration platform within the Databricks ecosystem.
• You will learn to design and implement data workloads using Directed Acyclic Graphs (DAGs), configure various scheduling options, and implement advanced workflow features such as conditional task execution, run-if dependencies, and for each loops.
• The course covers best practices for creating robust, production-ready pipelines with proper compute selection, modular orchestration, error handling techniques, and fault-tolerant design-all natively integrated within the Databricks Data Intelligence Platform.
3. Build Data Pipelines with Apache Spark Declarative Pipelines
This course introduces users to the essential concepts and skills needed to build data pipelines using Apache Spark Declarative Pipelines (SDP) in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Spark Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.
Topics covered include:
• Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
• How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
• Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
4. DevOps Essentials for Data Engineering
This course explores software engineering best practices and DevOps principles, specifically designed for data engineers working with Databricks. Participants will build a strong foundation in key topics such as code quality, version control, documentation, and testing. The course emphasizes DevOps, covering core components, benefits, and the role of continuous integration and delivery (CI/CD) in optimizing data engineering workflows.
You will learn how to apply modularity principles in PySpark to create reusable components and structure code efficiently. Hands-on experience includes designing and implementing unit tests for PySpark functions using the pytest framework, followed by integration testing for Databricks data pipelines with Spark Declarative Pipeline and Jobs to ensure reliability.
The course also covers essential Git operations within Databricks, including using Databricks Git Folders to integrate continuous integration practices. Finally, you will take a high level look at various deployment methods for Databricks assets, such as REST API, CLI, SDK, and Declarative Automation Bundles (DABs), providing you with the knowledge of techniques to deploy and manage your pipelines.
By the end of the course, you will be proficient in software engineering and DevOps best practices, enabling you to build scalable, maintainable, and efficient data engineering solutions.
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Throughout the course, you will dive into modern data ingestion and processing techniques, mastering tools like Liquid Clustering for layout optimization and the Multiplex Streaming pattern for mixed-schema events. By the end of the modules, you will know how to confidently handle schema evolution, automate Change Data Capture (CDC), and ensure data integrity.
Through lectures and hands-on demos, you will:
• Build multi-flow pipelines to ingest multi-source data into a unified Bronze table.
• Apply Liquid Clustering and Data Quality Expectations across Silver and Gold layers.
• Implement the Multiplex pattern with Iceberg UniForm for cross-platform data access.
• Automate SCD Type 2 history tracking using AUTO CDC INTO.
• Design zero-data-loss quarantine pipelines to audit and manage invalid records.
Note:
1. This course is part of the 'Advanced Data Engineering with Databricks' course series.
2. Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어
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Languages Available: English | 日本語 | 한국어
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Through hands-on projects, you will construct end-to-end distributed ML pipelines using the SparkML workflow, applying Transformers, Estimators, and the fit/transform paradigm for both classification and regression tasks. You will version, compare, and manage experiments using MLflow 3.0 to ensure reproducibility and governance, capturing lineage between data, features, and model artifacts. Additionally, you will apply scalable Hyperparameter Optimization frameworks to improve model performance at scale.
The course concludes by demonstrating complete lifecycle management, from experimentation to production deployment, using Unity Catalog and Model Serving. You will learn to operationalize trained models, monitor their performance, and implement strong governance over models, features, and Delta assets within the Databricks environment.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28244","entityUrl":{"path":"/training/catalog/catalog-management-and-data-organization-5261"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/catalog-management-and-data-organization-5261"}}],"nid":28244,"vid":217549,"title":"Catalog Management and Data Organization","price":"750.00","duration":14400,"body":{"processed":"In this course, you will learn how to design, implement, and govern catalog structures and large-scale data organization on the Databricks Data Intelligence Platform. It offers a comprehensive view of Unity Catalog as the centralized governance layer for an enterprise lakehouse. Divided into five modules, it begins by placing Unity Catalog within the cloud deployment model — covering the Account Console, metastore creation, and the administrator role hierarchy. You will then translate organizational topology (business units, regions, and dev/QA/prod environments) into a scalable catalog and schema design using naming conventions, ownership patterns, and MANAGE delegation. The course then covers secure storage integration with storage credentials, external locations, the managed-storage hierarchy, managed versus external tables, and UC Volumes for non-tabular data. Next, you will apply access patterns and isolation strategies — the three-level GRANT chain, workspace-catalog binding, and schema-level Attribute-Based Access Control (ABAC) policies — to enforce fine-grained data protection at scale. Finally, the course closes with best practices for catalog design, automation, least-privilege permissions, and group-based access management.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
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Languages Available: English | 日本語 | Português BR | 한국어 | Français
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.\n
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Below, we describe each of the four, four-hour modules included in this course.
Building RAG Agents with Agent Bricks: This course provides hands-on training for building retrieval agents using Databricks Agent Bricks. Participants will learn to explore and query Knowledge Assistants, parse unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, build Vector Search indexes, and create production-ready Knowledge Assistants backed by multiple knowledge sources.
Building Agentic Applications on Databricks: This course teaches students how to build production-grade agentic applications on Databricks. Students learn to create governed agent tools using Unity Catalog and MCP, build single and multi-agent systems with the OpenAI Agents SDK, and leverage Agent Bricks and Genie for knowledge-assistant use cases orchestrated with a supervisor agent. The course covers the full progression from tool prototyping to production deployment, with hands-on experience using MLflow tracing to observe agent execution.
Agent Evaluation on Databricks: This course teaches students how to systematically evaluate AI agents using MLflow's evaluation framework, addressing the unique challenges of non-deterministic AI systems that traditional software testing cannot handle. Students learn to implement various evaluation approaches including built-in judges for common criteria like correctness and safety, guideline judges for business-specific requirements, and custom judges for specialized needs. The course covers both offline evaluation using curated datasets and online production monitoring, with hands-on experience using MLflow's tracing capabilities to understand agent execution patterns and collect human feedback from different stakeholder types. Through practical demonstrations and labs, students develop skills in creating evaluation workflows that drive continuous quality improvements throughout the AI agent development lifecycle.
Deploying and Monitoring Agent Applications on Databricks: This course covers the end-to-end lifecycle for deploying and monitoring generative AI agents on Databricks. Participants will learn how to deploy agents as Databricks Apps using Declarative Automation Bundles (DABs), integrate tools via the Model Context Protocol (MCP), instrument agents with MLflow Tracing, and evaluate production quality using scorers, multi-turn judges, and online evaluation. Through hands-on demos and labs, participants will gain practical experience building, observing, and monitoring production-grade AI agents on the Databricks platform.
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Languages Available: English | 日本語 |한국어
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Through hands-on projects, you will construct end-to-end distributed ML pipelines using the SparkML workflow, applying Transformers, Estimators, and the fit/transform paradigm for both classification and regression tasks. You will version, compare, and manage experiments using MLflow 3.0 to ensure reproducibility and governance, capturing lineage between data, features, and model artifacts. Additionally, you will apply scalable Hyperparameter Optimization frameworks to improve model performance at scale.
The course concludes by demonstrating complete lifecycle management, from experimentation to production deployment, using Unity Catalog and Model Serving. You will learn to operationalize trained models, monitor their performance, and implement strong governance over models, features, and Delta assets within the Databricks environment.
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Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어
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You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.
Languages Available: English | 日本語 | Português BR| 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"28448","entityUrl":{"path":"/training/catalog/advanced-data-engineering-with-databricks-971"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/advanced-data-engineering-with-databricks-971"}}],"nid":28448,"vid":217753,"title":"Advanced Data Engineering with Databricks","price":"1500.00","duration":57600,"body":{"processed":"This course serves as an appropriate entry point to learn Advanced Data Engineering with Databricks.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures in the first and fourth module. You can access the lecture notebooks in the Vocareum lab environment.
Below, we describe each of the four, four-hour modules included in this course.
Advanced Techniques with Spark Declarative Pipelines
This course explores Databricks' Apache Spark Declarative Pipelines (SDP) for building production-grade streaming pipelines. You will learn advanced design patterns, robust data quality enforcement, and cross-platform integration essential for real-world lakehouse engineering.
Throughout the course, you will dive into modern data ingestion and processing techniques, mastering tools like Liquid Clustering for layout optimization and the Multiplex Streaming pattern for mixed-schema events. By the end of the modules, you will know how to confidently handle schema evolution, automate Change Data Capture (CDC), and ensure data integrity.
Through lectures and hands-on demos, you will:
• Build multi-flow pipelines to ingest multi-source data into a unified Bronze table.
• Apply Liquid Clustering and Data Quality Expectations across Silver and Gold layers.
• Implement the Multiplex pattern with Iceberg UniForm for cross-platform data access.
• Automate SCD Type 2 history tracking using AUTO CDC INTO.
• Design zero-data-loss quarantine pipelines to audit and manage invalid records.
Databricks Data Privacy
This content is intended for the learner persona of data engineers or for customers, partners, and employees who complete data engineering tasks with Databricks. It aims to provide them with the necessary knowledge and skills to execute these activities effectively on the Databricks platform.
Databricks Performance Optimization
In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.
Automated Deployment with Declarative Automation Bundles
This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.
The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.
Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.
Languages Available: English | 日本語 | Português BR | 한국어
\n \n
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Languages Available: English | 日本語 | Português BR | 한국어
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Languages Available: English | 日本語 | 한국어
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28304","entityUrl":{"path":"/training/catalog/databricks-performance-optimization-2958"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-performance-optimization-2958"}}],"nid":28304,"vid":217609,"title":"Databricks Performance Optimization","price":"75.00","duration":10800,"body":{"processed":"In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.
Note:
1. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
2. This course is part of the 'Advanced Data Engineering with Databricks' course series.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28399","entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-3605"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-3605"}}],"nid":28399,"vid":217704,"title":"DevOps Essentials for Data Engineering","price":"750.00","duration":14400,"body":{"processed":"This course explores software engineering best practices and DevOps principles, specifically designed for data engineers working with Databricks. Participants will build a strong foundation in key topics such as code quality, version control, documentation, and testing. The course emphasizes DevOps, covering core components, benefits, and the role of continuous integration and delivery (CI/CD) in optimizing data engineering workflows.
You will learn how to apply modularity principles in PySpark to create reusable components and structure code efficiently. Hands-on experience includes designing and implementing unit tests for PySpark functions using the pytest framework, followed by integration testing for Databricks data pipelines with Spark Declarative Pipeline and Jobs to ensure reliability.
The course also covers essential Git operations within Databricks, including using Databricks Git Folders to integrate continuous integration practices. Finally, you will take a high level look at various deployment methods for Databricks assets, such as REST API, CLI, SDK, and Declarative Automation Bundles (DABs), providing you with the knowledge of techniques to deploy and manage your pipelines.
By the end of the course, you will be proficient in software engineering and DevOps best practices, enabling you to build scalable, maintainable, and efficient data engineering solutions.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28484","entityUrl":{"path":"/training/catalog/machine-learning-model-development-2390"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-model-development-2390"}}],"nid":28484,"vid":217789,"title":"Machine Learning Model Development","price":"0.00","duration":7200,"body":{"processed":"This comprehensive course provides a practical guide to developing traditional machine learning models on Databricks, emphasizing hands-on demonstrations and workflows using popular ML libraries. Participants will explore key ML techniques, including regression and clustering, while leveraging Databricks' powerful capabilities. The course covers MLflow integration for model tracking, Databricks Feature Store for feature management, and Optuna for hyperparameter tuning. Additionally, participants will learn how to accelerate model development with Genie Code, Databricks' AI-powered coding assistant that uses natural language, MCP connections, instructions, and skills to guide the full ML lifecycle. By the end of the course, learners will have real-world, practical skills to develop, optimize, and deploy machine learning models efficiently in the Databricks environment.
Note:
In this course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions (including advanced recursive CTEs), session-scoped objects like temporary views and tables, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. You will also learn how to guarantee data consistency across these multi-step pipelines using ACID-compliant multi-statement transactions. Finally, you’ll discover how to encapsulate logic into SQL Stored Procedures and orchestrate complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-15T09:00:00"},"endDate":{"value":"2026-10-15T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-10-15T13:00:00"},"endDate":{"value":"2026-10-15T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"America/Los_Angeles"}},{"entity":{"startDate":{"value":"2026-11-25T13:00:00"},"endDate":{"value":"2026-11-25T17:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2026-12-16T13:00:00"},"endDate":{"value":"2026-12-16T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T13:00:00"},"timezone":"Asia/Singapore"}},{"entity":{"startDate":{"value":"2027-01-27T13:00:00"},"endDate":{"value":"2027-01-27T17:00:00"},"timezone":"America/New_York"}}]},{"id":"28223","entityUrl":{"path":"/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-4962"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-4962"}}],"nid":28223,"vid":217528,"title":"Building Semantic Models in Databricks with UC Metric Views","price":"750.00","duration":14400,"body":{"processed":"In this course, you’ll learn how to empower your data consumers to get validated business insights with less burden on you and the rest of your enterprise's data and AI team. Through building a semantic layer on top of your gold layer, you'll offer decision makers and business analysts the opportunity to explore key business performance indicators in novel ways, while still maintaining efficient data operations and enterprise-vetted metrics.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-20T13:00:00"},"endDate":{"value":"2026-10-20T17:00:00"},"timezone":"America/New_York"}},{"entity":{"startDate":{"value":"2026-10-27T09:00:00"},"endDate":{"value":"2026-10-27T13:00:00"},"timezone":"Asia/Kolkata"}},{"entity":{"startDate":{"value":"2026-11-19T09:00:00"},"endDate":{"value":"2026-11-19T13:00:00"},"timezone":"America/Los_Angeles"}},{"entity":{"startDate":{"value":"2026-11-26T13:00:00"},"endDate":{"value":"2026-11-26T17:00:00"},"timezone":"Australia/Sydney"}},{"entity":{"startDate":{"value":"2026-12-17T13:00:00"},"endDate":{"value":"2026-12-17T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2027-01-28T09:00:00"},"endDate":{"value":"2027-01-28T13:00:00"},"timezone":"Asia/Singapore"}},{"entity":{"startDate":{"value":"2027-01-28T13:00:00"},"endDate":{"value":"2027-01-28T17:00:00"},"timezone":"America/New_York"}}]},{"id":"28306","entityUrl":{"path":"/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-2965"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-2965"}}],"nid":28306,"vid":217611,"title":"Build Data Pipelines with Apache Spark Declarative Pipelines","price":"75.00","duration":10800,"body":{"processed":"This course introduces users to the essential concepts and skills needed to build data pipelines using Apache Spark™ Declarative Pipelines (SDP) in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Spark Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.
Topics covered include:
• Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
• How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
• Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28400","entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-3638"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/devops-essentials-for-data-engineering-3638"}}],"nid":28400,"vid":217705,"title":"DevOps Essentials for Data Engineering","price":"75.00","duration":10800,"body":{"processed":"This course explores software engineering best practices and DevOps principles, specifically designed for data engineers working with Databricks. Participants will build a strong foundation in key topics such as code quality, version control, documentation, and testing. The course emphasizes DevOps, covering core components, benefits, and the role of continuous integration and delivery (CI/CD) in optimizing data engineering workflows.
You will learn how to apply modularity principles in PySpark to create reusable components and structure code efficiently. Hands-on experience includes designing and implementing unit tests for PySpark functions using the pytest framework, followed by integration testing for Databricks data pipelines with Spark Declarative Pipeline and Jobs to ensure reliability.
The course also covers essential Git operations within Databricks, including using Databricks Git Folders to integrate continuous integration practices. Finally, you will take a high level look at various deployment methods for Databricks assets, such as REST API, CLI, SDK, and Declarative Automation Bundles (DABs), providing you with the knowledge of techniques to deploy and manage your pipelines.
By the end of the course, you will be proficient in software engineering and DevOps best practices, enabling you to build scalable, maintainable, and efficient data engineering solutions.
Note:
1. This is the fourth course in the 'Data Engineering with Databricks' series.
2. For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28451","entityUrl":{"path":"/training/catalog/databricks-platform-administration-fundamentals-1230"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/databricks-platform-administration-fundamentals-1230"}}],"nid":28451,"vid":217756,"title":"Databricks Platform Administration Fundamentals","price":"0.00","duration":5400,"body":{"processed":"In this course, you will learn the fundamentals of platform administration in the Databricks Data Intelligence Platform. It covers the Databricks architecture, security model, administrative roles, cloud resource management, and automation techniques. You will explore key administrative responsibilities, including managing workspaces, metastores, and external storage, while ensuring security through access controls and role-based privileges. Additionally, you will learn to automate administrative tasks using the Databricks SDK, CLI, and Terraform. The course includes hands-on demonstrations to reinforce concepts and streamline platform management. By the end, you will be equipped to efficiently administer, secure, and automate Databricks environments in your organization.
Note: Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28485","entityUrl":{"path":"/training/catalog/machine-learning-model-development-2391"},"entityTranslations":[{"entityLanguage":{"id":"en"},"entityUrl":{"path":"/training/catalog/machine-learning-model-development-2391"}}],"nid":28485,"vid":217790,"title":"Machine Learning Model Development","price":"75.00","duration":10800,"body":{"processed":"This comprehensive course provides a practical guide to developing traditional machine learning models on Databricks, emphasizing hands-on demonstrations and workflows using popular ML libraries. Participants will explore key ML techniques, including regression and clustering, while leveraging Databricks' powerful capabilities. The course covers MLflow integration for model tracking, Databricks Feature Store for feature management, and Optuna for hyperparameter tuning. Additionally, participants will learn how to accelerate model development with Genie Code, Databricks' AI-powered coding assistant that uses natural language, MCP connections, instructions, and skills to guide the full ML lifecycle. By the end of the course, learners will have real-world, practical skills to develop, optimize, and deploy machine learning models efficiently in the Databricks environment.
Note:
AI は、開発者が構築を求められるものを変えました。エージェント、コパイロット、そしてインテリジェントなツールが実験から本番運用へと移行し、作業はコードを書くことからモデル、データ、サービスをオーケストレーションすることへとシフトしています。このコースでは、データが存在する場所でエージェントアプリケーションを構築することで、断片化したスタックを繋ぎ合わせるインフラストラクチャのオーバーヘッドをどのように排除できるかを学びます。ガイド付きのアカウントブリーフィングデモを通じて、Databricks Apps、Lakebase、Agent Bricks（Genie Spaces、Knowledge Assistants、Supervisor Agents）が、本番運用対応のエージェントアプリケーションを提供するために、一元化されたガバナンスの効いたサーバーレス基盤上でどのように連携するかをご覧いただけます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33954","entityUrl":{"path":"/jp/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-japanese-6631"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-japanese-6631"}}],"nid":33954,"vid":254344,"title":"Building Databricks Apps with Genie Code and Lakebase - Japanese","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps を使用すると、インタラクティブなデータおよび AI アプリケーションを Databricks プラットフォーム上で直接構築・デプロイすることができます。しかし、AI を活用した開発を成功させるには、単にコードを生成するだけでは不十分であり、効果的なワークフローを確立することが重要です。
このハンズオンコースでは、Genie Code を AI 開発アシスタントとして活用しながら、Lakebase をバックエンドとする Databricks App をゼロから構築します。その過程で、AI を活用した開発における実践的かつ再現可能なアプローチを習得します。具体的には、コードを生成する前に意図を明確に定義すること、小さく検証可能な単位で作業を進めること、再利用可能な Genie Code Skills を活用すること、そして AI が生成した出力をそのまま受け入れるのではなく、レビューおよび改善すべき対象として扱うことを学びます。
Databricks App の作成とデプロイ、トランザクションストアとしての Lakebase データベースのプロビジョニングと接続、CRUD 操作の実装、そして Genie Code を活用した一般的な開発タスクの効率化を行います。コースの終了時には、動作するアプリケーションが完成するだけでなく、将来のソフトウェアプロジェクトにおいて AI と効果的に協働するための実践的な Framework も身に付けることができます。
注：Databricks Academyでは、Databricks環境内でのクラスルームセッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックには、Vocareumラボ環境からアクセスできます
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33960","entityUrl":{"path":"/jp/training/catalog/automated-deployment-with-databricks-asset-bundles-japanese-3955"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/automated-deployment-with-databricks-asset-bundles-japanese-3955"}}],"nid":33960,"vid":254351,"title":"Automated Deployment with Databricks Asset Bundles - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、DevOpsの原則とDatabricks projectへの応用について包括的に解説します。まず、DevOps、DataOps、継続的インテグレーション（CI）、継続的デプロイメント（CD）、テストといった中核概念の概要から始め、これらの原則をデータエンジニアリングパイプラインに適用する方法を探求します。
コースでは次に、CI/CDプロセス内での継続的デプロイに焦点を当て、プロジェクトデプロイのためのDatabricks REST API、SDK、CLIなどのツールを検証します。Databricks Asset Bundles（DAB）について学び、それらがCI/CDプロセスにどのように組み込まれるかを理解します。DABの主要コンポーネント、フォルダ構造、Databricks内の様々なターゲット環境へのデプロイを効率化する仕組みについて深く掘り下げます。さらに、Databricks CLIを使用して、異なる構成を持つ複数環境向けにDatabricks Asset Bundlesの変数追加、修正、検証、デプロイ、実行を行う方法も学びます。
最後に、本コースではVisual Studio Codeをインタラクティブ開発環境（IDE）として紹介し、Databricks Asset Bundlesのローカル環境でのビルド、テスト、デプロイを可能にすることで開発プロセスを最適化します。コースの締めくくりとして、GitHub Actionsを用いたデプロイパイプラインの自動化を紹介し、Databricks Asset Bundlesを用いたCI/CDワークフローの強化を図ります。
本コース修了時には、Databricks Asset Bundles を使用して Databricks projectのデプロイを自動化し、DevOps プラクティスを通じて効率性を向上させるスキルを身につけることができます。
注：このコースは「Databricksによる高度なデータエンジニアリング」シリーズの4回目です。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33896","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3771"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3771"}}],"nid":33896,"vid":254031,"title":"Get Started with Databricks for Generative AI - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform の実践的な入門として、Generative AI システムの構築およびデプロイに向けたキーコンポーネントと機能を中心に学習します。参加者は、Databricks がスケーラブルな Generative AI ソリューションの開発をどのように支援するかを学び、AI Search、Agent Framework、およびモデルのトラッキングとロギングのための MLflow の Generative AI 機能などのツールを探索します。このコースでは、Retrieval-Augmented Generation (RAG) パイプラインの構築と評価、Generative AI エージェントのデプロイ、およびパフォーマンスを最適化するための評価 Framework の活用について、ハンズオン形式で学ぶ機会が含まれています。コース修了時には、学習者は Databricks Data Intelligence Platform 上で一般的な Generative AI アプリケーションを設計、デプロイ、および監視するためのスキルを身につけることができます。
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33897","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3774"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3774"}}],"nid":33897,"vid":254032,"title":"Get Started with Databricks for Generative AI - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform の実践的な入門として、Generative AI システムの構築およびデプロイに向けたキーコンポーネントと機能を中心に学習します。参加者は、Databricks がスケーラブルな Generative AI ソリューションの開発をどのように支援するかを学び、AI Search、Agent Framework、およびモデルのトラッキングとロギングのための MLflow の Generative AI 機能などのツールを探索します。このコースでは、Retrieval-Augmented Generation (RAG) パイプラインの構築と評価、Generative AI エージェントのデプロイ、およびパフォーマンスを最適化するための評価 Framework の活用について、ハンズオン形式で学ぶ機会が含まれています。コース修了時には、学習者は Databricks Data Intelligence Platform 上で一般的な Generative AI アプリケーションを設計、デプロイ、および監視するためのスキルを身につけることができます。
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33342","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6523"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6523"}}],"nid":33342,"vid":252749,"title":"Get Started with Databricks: End to End - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースは、Databricks Data Intelligence Platform への包括的なハンズオン入門です。ワークスペースからスタートし、AI と機械学習の入門までを網羅する一連のエンドツーエンドの学習を通じて、Databricks でデータを扱うために必要な日常的なスキルを習得します。
コースの内容：
コースを修了すると、Databricks のナビゲーション、Unity Catalog でのデータの検索とガバナンス、AI アシスタンスを活用した SQL およびノートブックコードの記述、ダッシュボードの構築、Genie を使用したデータ探索を自信を持って行えるようになります。
注：SCORM講義ファイルの場合は、コンテンツを完了した後、SCORMウィンドウを閉じてください。「Next Lesson」ボタンはクリックしないでください。クリックすると、SCORMモジュールが完了として記録されない場合があります。
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33343","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6524"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6524"}}],"nid":33343,"vid":252750,"title":"Get Started with Databricks: End to End - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースは、Databricks Data Intelligence Platform への包括的なハンズオン入門です。ワークスペースからスタートし、AI と機械学習の入門までを網羅する一連のエンドツーエンドの学習を通じて、Databricks でデータを扱うために必要な日常的なスキルを習得します。
コースの内容：
コースを修了すると、Databricks のナビゲーション、Unity Catalog でのデータの検索とガバナンス、AI アシスタンスを活用した SQL およびノートブックコードの記述、ダッシュボードの構築、Genie を使用したデータ探索を自信を持って行えるようになります。
注：SCORM講義ファイルの場合は、コンテンツを完了した後、SCORMウィンドウを閉じてください。「Next Lesson」ボタンはクリックしないでください。クリックすると、SCORMモジュールが完了として記録されない場合があります。
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32130","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4603"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4603"}}],"nid":32130,"vid":251253,"title":"Get Started with Databricks Platform Administration - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platformにおけるプラットフォーム管理の基礎を学びます。Databricks環境内での効果的なデータガバナンスに不可欠なコンポーネントであるUnity Catalogの包括的な概要を提供します。5つのモジュールに分かれており、Databricksインフラストラクチャとdata intelligence platformの詳細な紹介から始まります。Databricks workspaceの詳細な操作手順も含まれます。Unity Catalog内のデータガバナンス原則を探求し、その主要な概念、アーキテクチャ、役割をカバーします。さらに、クラスターやSQLウェアハウスを含む、Unity Catalog metastoresとコンピューティングリソースの管理に重点を置きます。最後に、権限、きめ細かいアクセス制御、データオブジェクトのガバナンス手法を学び、データアクセス制御を習得します。修了時には、効果的なデータガバナンスの実装、コンピューティングリソースの最適化、堅牢なデータセキュリティ戦略の徹底に必要な、Unity Catalog管理の必須スキルを身につけます。Databricks Labsサブスクリプションを購入すると、コースの最後には、ライブのDatabricks workspace環境で学んだ内容を実践する包括的なラボ演習が用意されています。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"32119","entityUrl":{"path":"/jp/training/catalog/ai-agent-fundamentals-accreditation-japanese-4749"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/ai-agent-fundamentals-accreditation-japanese-4749"}}],"nid":32119,"vid":251046,"title":"AI Agent Fundamentals Accreditation - Japanese","price":"0.00","duration":1800,"body":{"processed":"AI Agents Fundamentals Accreditation この20問のクイズでは、AIエージェントの基礎知識、企業での応用方法、DatabricksのMosaic AIとAgent Bricksを用いた構築・展開手法について理解度を確認します。クイズを成功裏に完了すると、認定ベンダーAccredibleを通じてバッジが授与されます（48時間以内。)頑張ってください！
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32085","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6486"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6486"}}],"nid":32085,"vid":250756,"title":"Get Started with Databricks Apps - Japanese","price":"0.00","duration":3600,"body":{"processed":"このコースでは、開発者がセキュアなデータおよび AI アプリケーションを Databricks プラットフォーム上で直接構築・デプロイできる機能である Databricks Apps を紹介します。本コースは主に、データの知見を組織内の非技術系ユーザーがアクセスしやすい形にするカスタムアプリケーションを作成する必要があるデータサイエンティスト、データエンジニア、および開発者を対象としています。
コースはまず Databricks Apps の主要コンポーネントの概要を説明し、続いて外部サービスおよび Databricks リソースと連携するシンプルなアプリのデプロイを行います。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32087","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6489"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6489"}}],"nid":32087,"vid":250758,"title":"Get Started with Databricks Apps - Japanese","price":"75.00","duration":7200,"body":{"processed":"このコースでは、開発者がセキュアなデータおよび AI アプリケーションを Databricks プラットフォーム上で直接構築・デプロイできる機能である Databricks Apps を紹介します。本コースは主に、データの知見を組織内の非技術系ユーザーがアクセスしやすい形にするカスタムアプリケーションを作成する必要があるデータサイエンティスト、データエンジニア、および開発者を対象としています。
コースはまず Databricks Apps の主要コンポーネントの概要を説明し、続いて外部サービスおよび Databricks リソースと連携するシンプルなアプリのデプロイを行います。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32075","entityUrl":{"path":"/jp/training/catalog/databricks-fundamentals-japanese-2298"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-fundamentals-japanese-2298"}}],"nid":32075,"vid":250691,"title":"Databricks Fundamentals - Japanese","price":"0.00","duration":3600,"body":{"processed":"このコースは、Databricks および Databricks Platform への基礎的な入門コースです。現代のデータおよび AI チームが直面する課題、プラットフォームの中心にある lakehouse の考え方、プラットフォームが提供する製品と機能、統合ガバナンスによるデータと AI の信頼性の維持方法、そしてワークスペース自体のガイドツアーについて学びます。
これらの動画は推奨順に提供されていますが、ご希望の順序でご視聴いただいて構いません。また、Databricks Fundamentals の認定評価に挑戦する前に、利用可能なすべての動画コンテンツをご視聴されることをお勧めします。
Databricks やデータプラットフォームに関する事前の技術的知識は不要です。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32036","entityUrl":{"path":"/jp/training/catalog/data-governance-at-scale-japanese-6428"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-governance-at-scale-japanese-6428"}}],"nid":32036,"vid":250202,"title":"Data Governance at Scale - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Unity Catalog を使用して Databricks 上でデータガバナンスをスケールで実装する方法を学びます。属性ベースのアクセス制御、オブザーバビリティ、フェデレーテッド共有に重点を置いています。管理されたタグを使用した ABAC の設定、レガシーのきめ細かいコントロールからの移行、監査およびコストモニタリング用のシステムテーブルの有効化と使用、データおよびモデル品質のための Data Quality Monitoring のデプロイ、影響とコンプライアンスのためのリネージの解釈、セキュアなクロスクラウドコラボレーションのためのフェデレーテッドガバナンスと Delta Sharing パターンの適用について学習します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"32033","entityUrl":{"path":"/jp/training/catalog/generative-ai-fundamentals-japanese-2251"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/generative-ai-fundamentals-japanese-2251"}}],"nid":32033,"vid":250194,"title":"Generative AI Fundamentals - Japanese","price":"0.00","duration":7200,"body":{"processed":"Generative AI は、新興のエクスペリメントから企業に不可欠な機能へと進化し、インテリジェントなカスタマーサポートから複雑な Workflows を自動化する AI エージェントまで、あらゆる用途を支えています。
自社データを基盤とし、信頼性を確保したガバナンスのもとで効果的に導入する方法を理解している組織こそが、各産業界においてペースを牽引する存在となるでしょう。しかし、新しいモデルが毎週リリースされ、機能が急速に進化する中で、最新リリースを追いかけるよりも、GenAI を戦略的に評価し適用する方法を知ることの方が重要です。Generative AI の基礎—何ができるのか、どこで真のビジネス価値を生み出すのか、そして Databricks 上でいかに安全に実装するか—を、この無料のオンデマンドトレーニングで習得しましょう。
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31905","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-6441"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-6441"}}],"nid":31905,"vid":249968,"title":"Get Started with Databricks for Data Warehousing - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks のモダンなデータウェアハウジングアプローチについて、包括的かつハンズオン形式で概説します。データレイクハウスアーキテクチャが、従来のデータウェアハウスの強みとクラウドの柔軟性・スケーラビリティをどのように組み合わせているかを重点的に取り上げます。架空の小売業者（Vintage Audio Co.）を題材にエンドツーエンドで作業しながら、ワークスペースの探索、ガバナンスされた Unity Catalog テーブルへのクエリー、分析読み取りを高速に保つための Unity Catalog マネージドテーブルの最適化、Auto Loader を使ったインクリメンタルなデータ読み込み、スタースキーマのモデリング、そして Unity Catalog メトリクスビューを通じた一貫した知見の提供まで、すべてを単一のガバナンスされた環境から実施します。さらに、AI 駆動の機能（Predictive Optimization、Genie Code）が全体を通じて組み込まれています。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31906","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-6442"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-6442"}}],"nid":31906,"vid":249969,"title":"Get Started with Databricks for Data Warehousing - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks のモダンなデータウェアハウジングアプローチについて、包括的かつハンズオン形式で概説します。データレイクハウスアーキテクチャが、従来のデータウェアハウスの強みとクラウドの柔軟性・スケーラビリティをどのように組み合わせているかを重点的に取り上げます。架空の小売業者（Vintage Audio Co.）を題材にエンドツーエンドで作業しながら、ワークスペースの探索、ガバナンスされた Unity Catalog テーブルへのクエリー、分析読み取りを高速に保つための Unity Catalog マネージドテーブルの最適化、Auto Loader を使ったインクリメンタルなデータ読み込み、スタースキーマのモデリング、そして Unity Catalog メトリクスビューを通じた一貫した知見の提供まで、すべてを単一のガバナンスされた環境から実施します。さらに、AI 駆動の機能（Predictive Optimization、Genie Code）が全体を通じて組み込まれています。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31861","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6401"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-end-to-end-japanese-6401"}}],"nid":31861,"vid":249270,"title":"Get Started with Databricks: End to End - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースは、Databricks Data Intelligence Platform への包括的なハンズオン入門です。ワークスペースからスタートし、AI と機械学習の入門までを網羅する一連のエンドツーエンドの学習を通じて、Databricks でデータを扱うために必要な日常的なスキルを習得します。
コースの内容：
• Databricks ワークスペース、コンピュートオプション、および Lakehouse と Genie のエクスペリエンスのナビゲーション。
• Unity Catalog を使用したデータの理解とインジェスト（ファイルのアップロードや Catalog Explorer を含む）。
• Databricks ノートブックでの作業と、Genie Code を使用したコードの記述およびデバッグ。
• SQL によるデータのクエリ、保存済みクエリの管理、ダッシュボードおよびビジュアライゼーションの構築。
• Genie Agents を使用した自然言語によるデータの探索。
• MLflow と Data Science Agent を使用した AI および機械学習の入門。
コースを修了すると、Databricks のナビゲーション、Unity Catalog でのデータの検索とガバナンス、AI アシスタンスを活用した SQL およびノートブックコードの記述、ダッシュボードの構築、Genie を使用したデータ探索を自信を持って行えるようになります。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31802","entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3423"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3423"}}],"nid":31802,"vid":248571,"title":"Get Started with SQL Analytics and BI on Databricks - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform と、データアナリストが日常的な SQL アナリティクスおよび BI 業務に必要なコアスキルを紹介します。ワークスペースと Unity Catalog のナビゲーション、Serverless SQL Warehouse からの Unity Catalog マネージドテーブルに対する SQL クエリの記述、Genie Code を使用した SQL の生成とデバッグ、Delta Lake の操作（DML、バージョン履歴、タイムトラベル、およびリストア）、AI/BI ダッシュボードの構築と公開、そして会話型アナリティクスのための Genie Agents の作成について学習します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31803","entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3424"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3424"}}],"nid":31803,"vid":248572,"title":"Get Started with SQL Analytics and BI on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform と、データアナリストが日常的な SQL アナリティクスおよび BI 業務に必要なコアスキルを紹介します。ワークスペースと Unity Catalog のナビゲーション、Serverless SQL Warehouse からの Unity Catalog マネージドテーブルに対する SQL クエリの記述、Genie Code を使用した SQL の生成とデバッグ、Delta Lake の操作（DML、バージョン履歴、タイムトラベル、およびリストア）、AI/BI ダッシュボードの構築と公開、そして会話型アナリティクスのための Genie Agents の作成について学習します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31031","entityUrl":{"path":"/jp/training/catalog/building-agentic-applications-on-databricks-japanese-6055"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-agentic-applications-on-databricks-japanese-6055"}}],"nid":31031,"vid":246063,"title":"Building Agentic Applications on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks上で本番運用グレードのAgentic Applicationsを構築する方法を学びます。受講者は、Unity CatalogとMCPを使用してガバナンスが適用されたAgentツールを作成し、OpenAI Agents SDKで単一およびマルチAgentシステムを構築し、Supervisor AgentでオーケストレーションされるKnowledge AssistantのユースケースにAgent BricksとGenieを活用する方法を学びます。ツールのプロトタイピングから本番運用へのデプロイまでの全過程を扱い、MLflow tracingを使用してAgentの実行を観測するハンズオン経験を積みます。
注: SCORM講義ファイルでは、コンテンツを完了した後に必ずSCORMウィンドウを閉じてください。「次のレッスン」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として記録されない場合があります。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31032","entityUrl":{"path":"/jp/training/catalog/building-agentic-applications-on-databricks-japanese-6056"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-agentic-applications-on-databricks-japanese-6056"}}],"nid":31032,"vid":246064,"title":"Building Agentic Applications on Databricks - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks上で本番運用グレードのAgentic Applicationsを構築する方法を学びます。受講者は、Unity CatalogとMCPを使用してガバナンスが適用されたAgentツールを作成し、OpenAI Agents SDKで単一およびマルチAgentシステムを構築し、Supervisor AgentでオーケストレーションされるKnowledge AssistantのユースケースにAgent BricksとGenieを活用する方法を学びます。ツールのプロトタイピングから本番運用へのデプロイまでの全過程を扱い、MLflow tracingを使用してAgentの実行を観測するハンズオン経験を積みます。
注: SCORM講義ファイルでは、コンテンツを完了した後に必ずSCORMウィンドウを閉じてください。「次のレッスン」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として記録されない場合があります。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31010","entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-6227"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-6227"}}],"nid":31010,"vid":245973,"title":"SQL Programming and Procedural Logic - Japanese","price":"0.00","duration":7200,"body":{"processed":"本コースでは、Databricks 内のコアとなる SQL プログラミングと手続き型ロジックのスキルを学び、モジュラーで保守性が高く本番運用に対応したアナリティクスワークフローの構築方法に焦点を当てます。まず、Common Table Expressions(コモンテーブルエクスプレッション)（高度な再帰 CTE を含む）、一時ビューやテーブルなどのセッションスコープのオブジェクト、User Defined Functions(ユーザー定義関数) など、SQL 開発をよりクリーンで再利用しやすくする主要な SQL コンストラクトについて学びます。次に、複合ステートメント、変数、制御フロー、条件分岐、ループ、堅牢なエラーハンドリングを使用した高度な SQL スクリプティング技法を通じて、構造化された柔軟な SQL プロセスの作成方法を学びます。また、ACID 準拠の複数ステートメントトランザクションを使用して、これらの複数ステップのパイプライン全体でデータの一貫性を保証する方法も学びます。最後に、ロジックを SQL Stored Procedures(ストアドプロシージャ) にカプセル化し、Lakeflow ジョブと移行戦略で複雑なワークフローをオーケストレーションし、レガシータスクをモジュラーで自動化されたパイプラインに変換して Databricks platformの全機能を活用する方法を学びます。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31011","entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-6228"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-6228"}}],"nid":31011,"vid":245974,"title":"SQL Programming and Procedural Logic - Japanese","price":"75.00","duration":10800,"body":{"processed":"本コースでは、Databricks 内のコアとなる SQL プログラミングと手続き型ロジックのスキルを学び、モジュラーで保守性が高く本番運用に対応したアナリティクスワークフローの構築方法に焦点を当てます。まず、Common Table Expressions(コモンテーブルエクスプレッション)（高度な再帰 CTE を含む）、一時ビューやテーブルなどのセッションスコープのオブジェクト、User Defined Functions(ユーザー定義関数) など、SQL 開発をよりクリーンで再利用しやすくする主要な SQL コンストラクトについて学びます。次に、複合ステートメント、変数、制御フロー、条件分岐、ループ、堅牢なエラーハンドリングを使用した高度な SQL スクリプティング技法を通じて、構造化された柔軟な SQL プロセスの作成方法を学びます。また、ACID 準拠の複数ステートメントトランザクションを使用して、これらの複数ステップのパイプライン全体でデータの一貫性を保証する方法も学びます。最後に、ロジックを SQL Stored Procedures(ストアドプロシージャ) にカプセル化し、Lakeflow ジョブと移行戦略で複雑なワークフローをオーケストレーションし、レガシータスクをモジュラーで自動化されたパイプラインに変換して Databricks platformの全機能を活用する方法を学びます。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30884","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6201"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-apps-japanese-6201"}}],"nid":30884,"vid":245231,"title":"Get Started with Databricks Apps - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、開発者がセキュアなデータおよび AI アプリケーションを Databricks プラットフォーム上で直接構築・デプロイできる機能である Databricks Apps を紹介します。本コースは主に、データの知見を組織内の非技術系ユーザーがアクセスしやすい形にするカスタムアプリケーションを作成する必要があるデータサイエンティスト、データエンジニア、および開発者を対象としています。
コースはまず Databricks Apps の主要コンポーネントの概要を説明し、続いて外部サービスおよび Databricks リソースと連携するシンプルなアプリのデプロイを行います。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30836","entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5451"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5451"}}],"nid":30836,"vid":244563,"title":"Get Started with Lakebase - Japanese","price":"0.00","duration":7200,"body":{"processed":"このはじめようコースでは、Databricks Lakebase を紹介します。Databricks Lakebase は、Databricks Data Intelligence Platform に組み込まれたフルマネージド PostgreSQL サービスであり、運用系（OLTP）ワークロードとアナリティクス系（OLAP）ワークロードをより緊密に統合します。
コースはまず概念的な講義から始まり、OLTP システムと OLAP システムを比較しながら、それぞれのパフォーマンス特性、ストレージモデル、および代表的なユースケースについて説明します。また、データ移動、レイテンシー、アーキテクチャの複雑さなど、トランザクションデータベースとアナリティクスプラットフォームを別々に維持する際に組織が直面する課題についても探索します。
次に、Databricks Lakebase がこれらの課題にどのように対処するかを学びます。Lakebase は PostgreSQL 互換の運用データベースを提供し、Databricks Lakehouse と直接統合することで、運用アプリケーションとアナリティクスを統一されたプラットフォーム上で連携させることを可能にします。
ハンズオンラボでは、以下の内容を実施します。
オートスケーリングコンピュートを使用して Lakebase プロジェクトを作成・探索する
• ブランチ、モニタリング、構成設定を含む Lakebase UI を操作する
• Lakebase SQL Editor を使用してテーブルを作成し、クエリーを実行する
• Lakehouse Federation と外部カタログを使用して Databricks から Lakebase データをクエリーする
• Delta テーブルを Lakebase に同期することでリバース ETL を実行する
• Python から Lakebase に接続し、基本的な CRUD 操作を実行する
これははじめようコースであるため、Lakebase を操作するためのコアコンセプトと基本的なワークフローの理解に重点を置いています。Lakebase 上でフルスケールの本番運用アプリケーションを構築することは、本コースの範囲外となります。
コースの終わりには、Unity Catalog と Databricks Lakehouse を基盤とする単一のガバナンスされたプラットフォーム上で、Lakebase が組織の運用システムとアナリティクスを橋渡しする方法について理解できるようになります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30845","entityUrl":{"path":"/jp/training/catalog/building-rag-agents-with-agent-bricks-japanese-6030"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-rag-agents-with-agent-bricks-japanese-6030"}}],"nid":30845,"vid":244573,"title":"Building RAG Agents with Agent Bricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Agent Bricksを使用して取得Agentを構築するハンズオントレーニングを提供します。受講者は、Knowledge Assistantの探索とクエリー、AI Functionsを使用した非構造化ドキュメントから構造化データへの解析、セマンティック取得のためのテキストのチャンク化、AI Searchインデックスの構築、複数のナレッジソースを使用する本番運用対応のKnowledge Assistantの作成について学びます。
注: SCORM講義ファイルでは、コンテンツを完了した後に必ずSCORMウィンドウを閉じてください。「次のレッスン」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として記録されない場合があります。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30703","entityUrl":{"path":"/jp/training/catalog/get-started-with-ai-agents-on-databricks-japanese-6124"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-ai-agents-on-databricks-japanese-6124"}}],"nid":30703,"vid":241191,"title":"Get Started with AI Agents on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースは、AIエージェントの概要、現代のAIアプリケーションにおける役割、およびDatabricksプラットフォーム上でAIエージェントアプリケーションを構築する方法についての入門コースです。AIエージェントの原則、従来のAIシステムとの違い、およびそのキーコンポーネントの探索について学びます。インタラクティブなデモとハンズオンラボを通じて、Databricks AI と Agent Bricks を使用してDatabricks上でAIエージェントを構築、デプロイ、評価する方法を習得します。このコースを修了すると、Databricks Data + AI Platformを使用してAIエージェントを作成およびデプロイする方法を理解できるようになります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30696","entityUrl":{"path":"/jp/training/catalog/introduction-to-python-for-data-science-and-data-engineering-japanese-6113"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/introduction-to-python-for-data-science-and-data-engineering-japanese-6113"}}],"nid":30696,"vid":239716,"title":"Introduction to Python for Data Science and Data Engineering - Japanese","price":"1500.00","duration":57600,"body":{"processed":"このコースは、Python を初めて学ぶ方を対象に、プログラムを使ってデータを操作するための基礎を提供します。コースはプログラミングの式、変数、データ型の基本的な紹介から始まります。その後、条件文と制御文、関数、収集型、ループ、エラー処理、クラスへと進みます。外部ライブラリを使って Python を拡張する方法を学び、データ解析と可視化のための Pandas ライブラリの使用経験を積みます。これには、Apache Spark を使った Pandas Workflows のスケーリングも含まれます。最後に、クラウドコンピューティングの基礎を探索します。コース全体を通じて、ラボ演習による実践的な練習を行い、授業後にプログラミングの知識をさらに深めるための追加リソースも提供されます。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。\n
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30663","entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-6092"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-6092"}}],"nid":30663,"vid":239026,"title":"Lakebase App Integration and Management - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Apps を、Databricks のフルマネージドでクラウドネイティブな PostgreSQL プラットフォームである Lakebase と統合し、安全でエンタープライズ対応のアプリケーションワークフローを構築する方法を学びます。Databricks Apps と Lakebase の基礎知識を土台として、本コースでは PostgreSQL の基礎、Lakebase Autoscaling、安全な SQL の実践、安全な接続管理、ロールベースアクセス、Data API の統合、ブランチベースの開発に焦点を当てます。また、AppKit がこのワークフローの中でアプリケーション開発をどのように加速し、統合の概念から実装へとより効率的に進めるのに役立つかについても探ります。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30664","entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-6094"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-6094"}}],"nid":30664,"vid":239027,"title":"Lakebase App Integration and Management - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Apps を、Databricks のフルマネージドでクラウドネイティブな PostgreSQL プラットフォームである Lakebase と統合し、安全でエンタープライズ対応のアプリケーションワークフローを構築する方法を学びます。Databricks Apps と Lakebase の基礎知識を土台として、本コースでは PostgreSQL の基礎、Lakebase Autoscaling、安全な SQL の実践、安全な接続管理、ロールベースアクセス、Data API の統合、ブランチベースの開発に焦点を当てます。また、AppKit がこのワークフローの中でアプリケーション開発をどのように加速し、統合の概念から実装へとより効率的に進めるのに役立つかについても探ります。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"30611","entityUrl":{"path":"/jp/training/catalog/lakehouse-architecture-fundamentals-japanese-6076"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/lakehouse-architecture-fundamentals-japanese-6076"}}],"nid":30611,"vid":238737,"title":"Lakehouse Architecture Fundamentals - Japanese","price":"0.00","duration":3600,"body":{"processed":"『The Data Lakehouse For Dummies』をベースにしたコンセプトレベルのコースです。「データレイクハウスとは何かよくわからない」という状態から、データレイクハウスのアーキテクチャおよびその背後にある技術について実務的な会話ができるレベルへと学習者を導きます。レガシーアーキテクチャの限界、データレイクハウスとは何か、そのコアテクノロジー、そしてDatabricks上でdata intelligenceと統合ワークロードを実現する方法について学びます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30467","entityUrl":{"path":"/jp/training/catalog/answering-business-questions-with-databricks-genie-japanese-6025"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/answering-business-questions-with-databricks-genie-japanese-6025"}}],"nid":30467,"vid":237936,"title":"Answering Business Questions with Databricks Genie - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、組織のデータについて平易な言葉で質問し、管理された安全な回答を得ることができる会話型分析ツールである Databricks Genie を紹介します。 Genie Spaceとは何か、データを安全に保つ方法、最良の結果を得るためのベストプラクティスを学びます。 コースは、ビジネスの謎を調査するために競う実践的なゲームで締めくくられます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30419","entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-3276"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-3276"}}],"nid":30419,"vid":237406,"title":"Deploy Workloads with Lakeflow Jobs - Japanese","price":"75.00","duration":14400,"body":{"processed":"Deploy Workloads with Lakeflow Jobs コースでは、Databricks エコシステム内の統合オーケストレーションプラットフォームとして Lakeflow Jobs を使用し、データ、アナリティクス、および AI ワークフローをオーケストレーションおよび自動化する方法を学びます。
• 有向非環状グラフ（DAG）を使用したデータワークロードの設計と実装、各種スケジューリングオプションの設定、および条件付きタスク実行、run-if 依存関係、for each ループなどの高度なワークフロー機能の実装について学習します。
• 本コースでは、適切なコンピュート選択、モジュール式オーケストレーション、エラー処理技術、およびフォールトトレラント設計を備えた、堅牢で本番運用に対応したパイプラインを作成するためのベストプラクティスを取り上げます。これらはすべて Databricks Data Intelligence Platform 内にネイティブに統合されています。
注: SCORM の講義ファイルについては、コンテンツの完了後に SCORM ウィンドウを閉じてください。「Next Lesson（次のレッスン）」ボタンはクリックしないでください。クリックすると、SCORM モジュールが完了として記録されない場合があります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30420","entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-3277"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-3277"}}],"nid":30420,"vid":237407,"title":"Deploy Workloads with Lakeflow Jobs - Japanese","price":"0.00","duration":7200,"body":{"processed":"Deploy Workloads with Lakeflow Jobs コースでは、Databricks エコシステム内の統合オーケストレーションプラットフォームとして Lakeflow Jobs を使用し、データ、アナリティクス、および AI ワークフローをオーケストレーションおよび自動化する方法を学びます。
• 有向非環状グラフ（DAG）を使用したデータワークロードの設計と実装、各種スケジューリングオプションの設定、および条件付きタスク実行、run-if 依存関係、for each ループなどの高度なワークフロー機能の実装について学習します。
• 本コースでは、適切なコンピュート選択、モジュール式オーケストレーション、エラー処理技術、およびフォールトトレラント設計を備えた、堅牢で本番運用に対応したパイプラインを作成するためのベストプラクティスを取り上げます。これらはすべて Databricks Data Intelligence Platform 内にネイティブに統合されています。
注: SCORM の講義ファイルについては、コンテンツの完了後に SCORM ウィンドウを閉じてください。「Next Lesson（次のレッスン）」ボタンはクリックしないでください。クリックすると、SCORM モジュールが完了として記録されない場合があります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30410","entityUrl":{"path":"/jp/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-japanese-6011"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-japanese-6011"}}],"nid":30410,"vid":237345,"title":"Building Semantic Models in Databricks with UC Metric Views - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、データコンシューマーが検証済みのビジネス上の知見を得られるよう支援しながら、あなたや企業のデータおよび AI チームへの負担を軽減する方法を学びます。ゴールドレイヤーの上にセマンティックレイヤーを構築することで、意思決定者やビジネスアナリストがキーとなるビジネスパフォーマンス指標を新たな方法で探索できる機会を提供しつつ、効率的なデータ操作と企業が承認したメトリクスを維持することができます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30359","entityUrl":{"path":"/jp/training/catalog/generative-ai-engineering-with-databricks-japanese-2433"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/generative-ai-engineering-with-databricks-japanese-2433"}}],"nid":30359,"vid":236976,"title":"Generative AI Engineering with Databricks - Japanese","price":"1500.00","duration":57600,"body":{"processed":"本コースは、最新かつ最も普及しているフレームワークとDatabricksの機能を使用して生成AIアプリケーションを構築したいデータサイエンティスト、機械学習エンジニア、その他のデータ実務者を対象としています。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
以下では、本コースに含まれる4つの4時間モジュールについてそれぞれ説明します。
Building RAG Agents with Agent Bricks: 本コースでは、Databricks Agent Bricksを使用して検索エージェントを構築するための実践的なトレーニングを提供します。参加者は、Knowledge Assistantsの探索とクエリ、AI Functionsを使用した非構造化ドキュメントの構造化データへの解析、セマンティック検索のためのテキストのチャンク分割、Vector Searchインデックスの構築、および複数のナレッジソースに支えられた本番運用対応のKnowledge Assistantsの作成方法を学びます。
Building Agentic Applications on Databricks: 本コースでは、Databricks上で本番グレードのエージェントアプリケーションを構築する方法を学びます。受講者は、Unity CatalogとMCPを使用してガバナンスされたエージェントツールを作成し、OpenAI Agents SDKを使用してシングルエージェントおよびマルチエージェントシステムを構築し、スーパーバイザーエージェントによってオーケストレーションされるknowledge assistantのユースケースのためにAgent BricksとGenieを活用する方法を学びます。本コースは、ツールのプロトタイピングから本番環境へのデプロイまでの全過程を扱い、MLflowのトレーシングを使用してエージェントの実行を観察する実践的な経験を提供します。
Agent Evaluation on Databricks: 本コースでは、MLflowの評価フレームワークを使用してAIエージェントを体系的に評価する方法を学び、従来のソフトウェアテストでは対応できない非決定論的なAIシステム特有の課題に取り組みます。受講者は、正確性や安全性などの一般的な基準のための組み込みジャッジ(built-in judges)、ビジネス固有の要件のためのガイドラインジャッジ、専門的なニーズのためのカスタムジャッジなど、さまざまな評価アプローチを実装する方法を学びます。本コースでは、キュレーションされたデータセットを使用したオフライン評価と、オンラインの本番モニタリングの両方を扱い、MLflowのトレーシング機能を使用してエージェントの実行パターンを理解し、さまざまなタイプのステークホルダーから人間のフィードバックを収集する実践的な経験を提供します。実践的なデモとラボを通じて、受講者はAIエージェントの開発ライフサイクル全体にわたって継続的な品質改善を推進する評価ワークフローを作成するスキルを習得します。
Deploying and Monitoring Agent Applications on Databricks: 本コースでは、Databricks上で生成AIエージェントをデプロイおよびモニタリングするためのエンドツーエンドのライフサイクルを扱います。参加者は、Declarative Automation Bundles(DABs)を使用してエージェントをDatabricks Appsとしてデプロイし、Model Context Protocol(MCP)を介してツールを統合し、MLflow Tracingでエージェントを計装し、スコアラー、マルチターンジャッジ、オンライン評価を使用して本番品質を評価する方法を学びます。実践的なデモとラボを通じて、参加者はDatabricksプラットフォーム上で本番グレードのAIエージェントを構築、観察、モニタリングする実践的な経験を得ます。
Languages Available: English | 日本語 | Português BR | 한국어
このコースでは、Databricks上で本番運用グレードのAgentic Applicationsを構築する方法を学びます。受講者は、Unity CatalogとMCPを使用してガバナンスが適用されたAgentツールを作成し、OpenAI Agents SDKで単一およびマルチAgentシステムを構築し、Supervisor AgentでオーケストレーションされるKnowledge AssistantのユースケースにAgent BricksとGenieを活用する方法を学びます。ツールのプロトタイピングから本番運用へのデプロイまでの全過程を扱い、MLflow tracingを使用してAgentの実行を観測するハンズオン経験を積みます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2027-01-19T14:00:00"},"endDate":{"value":"2027-01-19T18:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"30306","entityUrl":{"path":"/jp/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-japanese-5965"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-japanese-5965"}}],"nid":30306,"vid":236666,"title":"Deploying and Monitoring Agent Applications on Databricks - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricksで生成AI Agentをデプロイおよびモニタリングするためのエンドツーエンドのライフサイクルを扱います。受講者は、Declarative Automation Bundles（DABs）を使用してAgentをDatabricks Appsとしてデプロイする方法、Model Context Protocol（MCP）を介してツールを統合する方法、MLflow TracingでAgentを計装する方法、ならびにスコアラー、マルチターンジャッジ、オンライン評価を使用して本番運用品質を評価する方法を学びます。ハンズオン形式のデモとラボを通じて、Databricksプラットフォーム上で本番運用グレードのAI Agentを構築、観測、モニタリングする実践的な経験を積みます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-01T09:00:00"},"endDate":{"value":"2026-10-01T13:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-27T14:00:00"},"endDate":{"value":"2027-01-27T18:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"29872","entityUrl":{"path":"/jp/training/catalog/building-rag-agents-with-agent-bricks-japanese-5947"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-rag-agents-with-agent-bricks-japanese-5947"}}],"nid":29872,"vid":235719,"title":"Building RAG Agents with Agent Bricks - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks Agent Bricksを使用して取得Agentを構築するハンズオントレーニングを提供します。受講者は、Knowledge Assistantの探索とクエリー、AI Functionsを使用した非構造化ドキュメントから構造化データへの解析、セマンティック取得のためのテキストのチャンク化、AI Searchインデックスの構築、複数のナレッジソースを使用する本番運用対応のKnowledge Assistantの作成について学びます。
注意：Databricks Academyでは、Databricks環境内での教室セッションにおいて、ノートブックベースの形式への移行を進めており、講義でのスライドデッキの使用を廃止しています。講義ノートブックはVocareumのラボ環境からアクセスできます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-12-22T14:00:00"},"endDate":{"value":"2026-12-22T18:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"29797","entityUrl":{"path":"/jp/training/catalog/aibi-for-data-analysts-japanese-4187"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/aibi-for-data-analysts-japanese-4187"}}],"nid":29797,"vid":234757,"title":"AI/BI for Data Analysts - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、データアナリストが Databricks で AI/BI Dashboards を設計、作成、公開、運用する方法を学びます。AI/BI Dashboards は、ガバナンスの効いた Unity Catalog のデータを、インタラクティブな可視化、フィルター、Genie 連携と組み合わせることで、ビジネスユーザーがコードを書かずに回答を探索できるようにします。
このコースは、1 つのエンドツーエンドの構築を通じて進めます。まず Unity Catalog のソーステーブルから始め、最終的に公開・監視された複数ページのダッシュボードを完成させます。その過程で、ダッシュボードが Databricks の AI/BI 製品ファミリー全体の中でどのように位置づけられるか、また Genie、データセット、可視化、フィルターがワークフローのどこに当てはまるかを学びます。
扱う内容は次のとおりです。
• AI/BI Dashboards の基礎と、それが Genie および Databricks プラットフォームの他の要素とどのように関係するか。
• Unity Catalog でのソースデータの探索と、SQL を使用した再利用可能なダッシュボードデータセットの設計。
• 可視化（KPI、トレンド、内訳）の作成と、見やすい複数ページのダッシュボードのレイアウト。
• Genie Code を使用して、自然言語のプロンプトから SQL、チャート、フィルターを作成すること。
• フィルターを追加して、ダッシュボードをインタラクティブにし、閲覧者の疑問に応えられるようにすること。
• 適切な人がダッシュボードを表示・編集できるよう、公開、共有、アクセス権の管理を行うこと。
• スケジュールされた更新、キャッシュ、使用状況の監視を伴って、ダッシュボードを本番環境で運用すること。
コースを修了するころには、ビジネス上の課題を起点として、それを支えるデータセットを設計し、洗練されたダッシュボードを作成し、適切なアクセス権と、正確性を保つための更新戦略とともに対象ユーザーへ提供できるようになります。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
このコースでは、データアナリストが Databricks で AI/BI Dashboards を設計、作成、公開、運用する方法を学びます。AI/BI Dashboards は、ガバナンスの効いた Unity Catalog のデータを、インタラクティブな可視化、フィルター、Genie 連携と組み合わせることで、ビジネスユーザーがコードを書かずに回答を探索できるようにします。
このコースは、1 つのエンドツーエンドの構築を通じて進めます。まず Unity Catalog のソーステーブルから始め、最終的に公開・監視された複数ページのダッシュボードを完成させます。その過程で、ダッシュボードが Databricks の AI/BI 製品ファミリー全体の中でどのように位置づけられるか、また Genie、データセット、可視化、フィルターがワークフローのどこに当てはまるかを学びます。
扱う内容は次のとおりです。
• AI/BI Dashboards の基礎と、それが Genie および Databricks プラットフォームの他の要素とどのように関係するか。
• Unity Catalog でのソースデータの探索と、SQL を使用した再利用可能なダッシュボードデータセットの設計。
• 可視化（KPI、トレンド、内訳）の作成と、見やすい複数ページのダッシュボードのレイアウト。
• Genie Code を使用して、自然言語のプロンプトから SQL、チャート、フィルターを作成すること。
• フィルターを追加して、ダッシュボードをインタラクティブにし、閲覧者の疑問に応えられるようにすること。
• 適切な人がダッシュボードを表示・編集できるよう、公開、共有、アクセス権の管理を行うこと。
• スケジュールされた更新、キャッシュ、使用状況の監視を伴って、ダッシュボードを本番環境で運用すること。
コースを修了するころには、ビジネス上の課題を起点として、それを支えるデータセットを設計し、洗練されたダッシュボードを作成し、適切なアクセス権と、正確性を保つための更新戦略とともに対象ユーザーへ提供できるようになります。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29783","entityUrl":{"path":"/jp/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-japanese-5907"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-japanese-5907"}}],"nid":29783,"vid":234630,"title":"Business Impact Accelerator: Answering Business Questions with Genie - Japanese","price":"0.00","duration":10800,"body":{"processed":"
このコースでは、Databricks Genie One を紹介します。Genie One は AI を活用したコワーク環境であり、お客様のニーズと業務を中心に設計されています。組織のデータについて平易な言葉で質問し、ガバナンスの効いた安全な回答を得たり、レポートを自動的に実行するようスケジュールを設定したり、ワークフローを自動化してより多くの作業をより速く、より正確に完了させることができます。これはお客様のデータとビジネスに基づいているためです。このコースでは、Genie、Genie One、および Genie Agents とは何か、それらがどのようにデータを安全に保つか、そして最良の結果を得るためのベストプラクティスについて学びます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29755","entityUrl":{"path":"/jp/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-japanese-3731"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-japanese-3731"}}],"nid":29755,"vid":234457,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI) - Japanese","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
このコースでは、Databricks Data Intelligence Platform で基本的なデータエンジニアリングのワークフローを実行するために必要な基礎スキルを学びます。ワークスペースを操作し、Unity Catalog を使用しながら、データエンジニアが Databricks で日常的に活用する基本的な構成要素を習得します。
このコースは実践的な構成になっています。まずワークスペースの基本を理解し、その後、各トピックについてデモとラボのノートブックをペアで進めていきます。デモではインストラクターまたはガイド付きノートブックとともに概念を確認し、ラボでは学んだ内容を自分自身で実践します。
Get Started with SQL Analytics and BI on Databricks
このコースでは、Databricks Data Intelligence Platform を使用してシンプルなデータ分析ワークフローを実行し、データ ウェアハウスの取り組みをサポートするための基本的なスキルを学習します。 ワークスペースのツアーが提供され、カタログ、スキーマ、テーブル、コンピューティング クラスター、ノートブック、ダッシュボードなどのDatabricksのデータ オブジェクトを操作する方法が示されます。 次に、基本的なデータ分析workflowに従って、Databricks SQLを使用してデータを操作したり、Delta Lakeバージョン ログを利用してタイム トラベルしたり、プラットフォーム内でダッシュボードを作成したり、自然言語プロンプトを使用してデータ探索用のジニースペースを作成したりといったタスクを実行します。 また、Databricks SQL、Delta Live Tables、Unity Catalogを使用して、Databricksがデータ ウェアハウスのニーズをどのようにサポートするかについても学習します。 Databricks Labsサブスクリプションを購入すると、コースの最後には、学習した内容をライブDatabricks Workspace環境で実践する総合的なラボ演習も実施されます。
Databricks Free Editionアカウント を作成すれば、実践的な環境でデモを実際に試すことができます。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-29T13:00:00"},"endDate":{"value":"2026-10-29T17:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-11-19T13:00:00"},"endDate":{"value":"2026-11-19T17:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-21T13:00:00"},"endDate":{"value":"2027-01-21T17:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"29752","entityUrl":{"path":"/jp/training/catalog/catalog-management-and-data-organization-japanese-5892"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/catalog-management-and-data-organization-japanese-5892"}}],"nid":29752,"vid":234436,"title":"Catalog Management and Data Organization - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform上でカタログ構造と大規模なデータ組織化を設計、実装、ガバナンスする方法を学びます。エンタープライズlakehouseの集中型ガバナンスレイヤーとしてのUnity Catalogの包括的な概要を提供します。5つのモジュールに分かれており、クラウドデプロイメントモデル内でのUnity Catalogの位置づけから始まります。アカウントコンソール、メタストアの作成、管理者ロール階層をカバーします。次に、組織トポロジー（ビジネスユニット、リージョン、dev/QA/prod環境）を、命名規則、所有権パターン、MANAGE委任を使用したスケーラブルなカタログとスキーマ設計に変換します。コースは、ストレージクレデンシャル、外部ロケーション、managed-storage階層、マネージドテーブルと外部テーブル、非テーブルデータのUC Volumesを使用した安全なストレージ統合をカバーします。次に、アクセスパターンと分離戦略（3レベルのGRANTチェーン、ワークスペース-カタログバインディング、スキーマレベルの属性ベースアクセス制御（ABAC）ポリシー）を適用し、大規模なきめ細かいデータ保護を実施します。最後に、カタログ設計、自動化、最小権限、グループベースのアクセス管理のベストプラクティスで締めくくります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29621","entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-5841"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/lakebase-app-integration-and-management-japanese-5841"}}],"nid":29621,"vid":234127,"title":"Lakebase App Integration and Management - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks Apps を、Databricks のフルマネージドでクラウドネイティブな PostgreSQL プラットフォームである Lakebase と統合し、安全でエンタープライズ対応のアプリケーションワークフローを構築する方法を学びます。Databricks Apps と Lakebase の基礎知識を土台として、本コースでは PostgreSQL の基礎、Lakebase Autoscaling、安全な SQL の実践、安全な接続管理、ロールベースアクセス、Data API の統合、ブランチベースの開発に焦点を当てます。また、AppKit がこのワークフローの中でアプリケーション開発をどのように加速し、統合の概念から実装へとより効率的に進めるのに役立つかについても探ります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29630","entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-5861"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-programming-and-procedural-logic-japanese-5861"}}],"nid":29630,"vid":234136,"title":"SQL Programming and Procedural Logic - Japanese","price":"750.00","duration":14400,"body":{"processed":"本コースでは、Databricks 内のコアとなる SQL プログラミングと手続き型ロジックのスキルを学び、モジュラーで保守性が高く本番運用に対応したアナリティクスワークフローの構築方法に焦点を当てます。まず、Common Table Expressions(コモンテーブルエクスプレッション)（高度な再帰 CTE を含む）、一時ビューやテーブルなどのセッションスコープのオブジェクト、User Defined Functions(ユーザー定義関数) など、SQL 開発をよりクリーンで再利用しやすくする主要な SQL コンストラクトについて学びます。次に、複合ステートメント、変数、制御フロー、条件分岐、ループ、堅牢なエラーハンドリングを使用した高度な SQL スクリプティング技法を通じて、構造化された柔軟な SQL プロセスの作成方法を学びます。また、ACID 準拠の複数ステートメントトランザクションを使用して、これらの複数ステップのパイプライン全体でデータの一貫性を保証する方法も学びます。最後に、ロジックを SQL Stored Procedures(ストアドプロシージャ) にカプセル化し、Lakeflow ジョブと移行戦略で複雑なワークフローをオーケストレーションし、レガシータスクをモジュラーで自動化されたパイプラインに変換して Databricks platformの全機能を活用する方法を学びます。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29632","entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-5871"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-5871"}}],"nid":29632,"vid":234138,"title":"Machine Learning Model Development - Japanese","price":"75.00","duration":10800,"body":{"processed":"この包括的なコースでは、Databricks で従来の機械学習モデルを開発するための実践的なガイドを提供し、一般的な ML ライブラリを使用した実践的なデモンストレーションとワークフローに重点を置いています。 参加者は、Databricks の強力な機能を活用しながら、回帰やクラスタリングなどの主要な機械学習手法を学習します。 このコースでは、モデル追跡のためのMLflow統合、機能管理のためのDatabricks Feature Store、ハイパーパラメーター調整のためのOptunaについて説明します。 さらに、参加者は、自然言語、MCP 接続、指示、スキルを使用して機械学習ライフサイクル全体をガイドする Databricks の AI 搭載コーディングアシスタントである Genie Code を使用して、モデル開発を加速する方法を学びます。 このコースを修了すると、学習者は Databricks 環境で機械学習モデルを効率的に開発、最適化、デプロイするための実践的なスキルを身に付けることができます。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"29633","entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-5872"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-5872"}}],"nid":29633,"vid":234139,"title":"Machine Learning Model Development - Japanese","price":"0.00","duration":7200,"body":{"processed":"この包括的なコースでは、Databricks で従来の機械学習モデルを開発するための実践的なガイドを提供し、一般的な ML ライブラリを使用した実践的なデモンストレーションとワークフローに重点を置いています。 参加者は、Databricks の強力な機能を活用しながら、回帰やクラスタリングなどの主要な機械学習手法を学習します。 このコースでは、モデル追跡のためのMLflow統合、機能管理のためのDatabricks Feature Store、ハイパーパラメーター調整のためのOptunaについて説明します。 さらに、参加者は、自然言語、MCP 接続、指示、スキルを使用して機械学習ライフサイクル全体をガイドする Databricks の AI 搭載コーディングアシスタントである Genie Code を使用して、モデル開発を加速する方法を学びます。 このコースを修了すると、学習者は Databricks 環境で機械学習モデルを効率的に開発、最適化、デプロイするための実践的なスキルを身に付けることができます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29420","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-3495"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-3495"}}],"nid":29420,"vid":232485,"title":"Get Started with Databricks for Data Engineering - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform で基本的なデータエンジニアリングのワークフローを実行するために必要な基礎スキルを学びます。ワークスペースを操作し、Unity Catalog を使用しながら、データエンジニアが Databricks で日常的に活用する基本的な構成要素を習得します。
このコースは実践的な構成になっています。まずワークスペースの基本を理解し、その後、各トピックについてデモとラボのノートブックをペアで進めていきます。デモではインストラクターまたはガイド付きノートブックとともに概念を確認し、ラボでは学んだ内容を自分自身で実践します。
このコースで扱う内容は次のとおりです。
• Databricks Data Intelligence Platform の概要と、Databricks workspace、Unity Catalog、ノートブックの連携方法。
• Delta Lake テーブルの作成と管理。
• INSERT、UPDATE、DELETE によるデータの変更。
• Delta テーブルのバージョン履歴とタイムトラベルの確認。
• Lakeflow Connect のオプション（CTAS、アップロード UI、COPY INTO）を使用したデータの取り込み。
• ブロンズ、シルバー、ゴールド の各レイヤーを通じてデータを変換するメダリオンアーキテクチャのパイプラインの構築。
• Lakeflow ジョブ によるパイプラインの自動化。
• （ボーナス）Spark Declarative Pipelines を使用した宣言型パイプラインの構築。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29421","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-3502"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-3502"}}],"nid":29421,"vid":232486,"title":"Get Started with Databricks for Data Engineering - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform で基本的なデータエンジニアリングのワークフローを実行するために必要な基礎スキルを学びます。ワークスペースを操作し、Unity Catalog を使用しながら、データエンジニアが Databricks で日常的に活用する基本的な構成要素を習得します。
このコースは実践的な構成になっています。まずワークスペースの基本を理解し、その後、各トピックについてデモとラボのノートブックをペアで進めていきます。デモではインストラクターまたはガイド付きノートブックとともに概念を確認し、ラボでは学んだ内容を自分自身で実践します。
このコースで扱う内容は次のとおりです。
• Databricks Data Intelligence Platform の概要と、Databricks workspace、Unity Catalog、ノートブックの連携方法。
• Delta Lake テーブルの作成と管理。
• INSERT、UPDATE、DELETE によるデータの変更。
• Delta テーブルのバージョン履歴とタイムトラベルの確認。
• Lakeflow Connect のオプション（CTAS、アップロード UI、COPY INTO）を使用したデータの取り込み。
• ブロンズ、シルバー、ゴールド の各レイヤーを通じてデータを変換するメダリオンアーキテクチャのパイプラインの構築。
• Lakeflow ジョブ によるパイプラインの自動化。
• （ボーナス）Spark Declarative Pipelines を使用した宣言型パイプラインの構築。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29318","entityUrl":{"path":"/jp/training/catalog/building-enterprise-applications-with-databricks-apps-japanese-5621"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-enterprise-applications-with-databricks-apps-japanese-5621"}}],"nid":29318,"vid":230163,"title":"Building Enterprise Applications with Databricks Apps - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、開発者が安全なデータおよび AI アプリケーションを Databricks プラットフォーム上に直接構築・デプロイできるようにする新機能、Databricks Apps を紹介します。主に、組織内の非技術系ユーザーがデータから得られる知見を活用できるカスタムアプリケーションを作成する必要がある、データサイエンティスト、データエンジニア、開発者を対象としています。
コースはまず、Databricks Apps の主要なコンポーネントの概要から始まり、続いて外部サービスと連携するシンプルなアプリのデプロイを行います。次に、Databricks プラットフォームの機能と統合された、インテリジェントでデータドリブンなアプリケーションを構築・デプロイする方法を学びます。その後、Databricks 環境の外でアプリを開発する方法を扱います。最後に、安全で信頼性の高いエンタープライズアプリを実装するためのベストプラクティスを詳しく解説して締めくくります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 한국어 | Español | française | Português BR
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29222","entityUrl":{"path":"/jp/training/catalog/architecting-data-warehouses-for-large-scale-deployments-japanese-5497"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/architecting-data-warehouses-for-large-scale-deployments-japanese-5497"}}],"nid":29222,"vid":229404,"title":"Architecting Data Warehouses for Large-Scale Deployments - Japanese","price":"750.00","duration":14400,"body":{"processed":"本コースでは、大規模なデータウェアハウス環境のパフォーマンス最適化、コスト管理、およびセキュリティについて解説します。
本コースは、複数の事業部門にまたがり数百人から数千人のユーザーにサービスを提供するDatabricks環境の管理を担当するデータウェアハウス実務者を対象としています。本コースを受講することで、高いパフォーマンスとコスト効率を維持しつつ、セキュリティ基準への準拠を確保しながら、データウェアハウス運用を効率的に拡張するために必要なスキルを習得できます。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29207","entityUrl":{"path":"/jp/training/catalog/building-reliable-conversational-agents-with-genie-japanese-5566"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-reliable-conversational-agents-with-genie-japanese-5566"}}],"nid":29207,"vid":229263,"title":"Building Reliable Conversational Agents with Genie - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks の Genie Space の設計、構築および保守の方法を学びます。Genie Space は、ビジネスユーザーがガバナンスされたデータについて質問し、コードを書かずに SQL に基づく回答を受け取れる自然言語インターフェースです。
Genie が Databricks の AI/BI 製品ファミリーにどのように位置づけられるか、そして自然言語をどのように信頼できる SQL クエリに変換するかを学びます。このコースでは、正確で一貫性があり、信頼できる結果を提供する Genie Space を作成するために何が必要かに焦点を当てます。
ソースデータの理解とベンチマークの定義から、ナレッジストア のキュレーションツール一式を使った Genie Space の構成と改良まで、完全なエンドツーエンドのワークフローをたどります。これらのツールには、メタデータ、シノニム、プロンプトマッチング、SQL ロジック、サンプルクエリ、テキストの 手順 が含まれます。
また、Databricks One を通じてビジネスユーザーと Genie Space を共有する方法、Unity Catalog のガバナンスがどのように自動的に適用されるかを理解し、モニタリングとユーザーのフィードバックを使って品質を継続的に改善する方法も学びます。
コースを終える頃には、ガバナンスされたセルフサービスの会話型分析を大規模に提供する、本番運用の準備が整った Genie Space を作成および管理できるようになります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29205","entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5448"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5448"}}],"nid":29205,"vid":229245,"title":"Get Started with Lakebase - Japanese","price":"0.00","duration":7200,"body":{"processed":"このはじめようコースでは、Databricks Lakebase を紹介します。Databricks Lakebase は、Databricks Data Intelligence Platform に組み込まれたフルマネージド PostgreSQL サービスであり、運用系（OLTP）ワークロードとアナリティクス系（OLAP）ワークロードをより緊密に統合します。
コースはまず概念的な講義から始まり、OLTP システムと OLAP システムを比較しながら、それぞれのパフォーマンス特性、ストレージモデル、および代表的なユースケースについて説明します。また、データ移動、レイテンシー、アーキテクチャの複雑さなど、トランザクションデータベースとアナリティクスプラットフォームを別々に維持する際に組織が直面する課題についても探索します。
次に、Databricks Lakebase がこれらの課題にどのように対処するかを学びます。Lakebase は PostgreSQL 互換の運用データベースを提供し、Databricks Lakehouse と直接統合することで、運用アプリケーションとアナリティクスを統一されたプラットフォーム上で連携させることを可能にします。
これははじめようコースであるため、Lakebase を操作するためのコアコンセプトと基本的なワークフローの理解に重点を置いています。Lakebase 上でフルスケールの本番運用アプリケーションを構築することは、本コースの範囲外となります。
コースの終わりには、Unity Catalog と Databricks Lakehouse を基盤とする単一のガバナンスされたプラットフォーム上で、Lakebase が組織の運用システムとアナリティクスを橋渡しする方法について理解できるようになります。
Databricks Free Edition のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29143","entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5514"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5514"}}],"nid":29143,"vid":228404,"title":"Building ETL Pipelines with SQL - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform で純粋な SQL を使用して、本番運用に対応した ETL パイプラインを構築する方法を学びます。 受講者は、増分インジェストのための Auto Loader を使用したストリーミングテーブル、Silver-to-Gold 変換のための増分更新を伴うマテリアライズドビュー、宣言型 SCD タイプ 1 およびタイプ 2 ディメンション管理のための AUTO CDC (FLOW AUTO CDC)、および本番オーケストレーションのための SQL ファイルタスクを使用した Lakeflow ジョブについて学習します。 このコースでは、メダリオンアーキテクチャ(ブロンズ → シルバー → ゴールド)を通じて、現実的な小売データセットに従います。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29142","entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5510"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5510"}}],"nid":29142,"vid":228403,"title":"Building ETL Pipelines with SQL - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform で純粋な SQL を使用して、本番運用に対応した ETL パイプラインを構築する方法を学びます。 受講者は、増分インジェストのための Auto Loader を使用したストリーミングテーブル、Silver-to-Gold 変換のための増分更新を伴うマテリアライズドビュー、宣言型 SCD タイプ 1 およびタイプ 2 ディメンション管理のための AUTO CDC (FLOW AUTO CDC)、および本番オーケストレーションのための SQL ファイルタスクを使用した Lakeflow ジョブについて学習します。 このコースでは、メダリオンアーキテクチャ(ブロンズ → シルバー → ゴールド)を通じて、現実的な小売データセットに従います。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28964","entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5474"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/building-etl-pipelines-with-sql-japanese-5474"}}],"nid":28964,"vid":226680,"title":"Building ETL Pipelines with SQL - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform 上で純粋な SQL を使用して、本番運用に対応した ETL パイプラインを構築する方法を学びます。受講者は、増分取り込みのための Auto Loader を使用したストリーミングテーブル、シルバーからゴールドへの変換処理のための増分更新付きマテリアライズドビュー、宣言的な SCD Type 1 および Type 2 ディメンション管理のための AUTO CDC（FLOW AUTO CDC）、そしてデータ品質の期待値、PRIVATE テーブル、統合モニタリングを備えた本番運用のマルチテーブルパイプラインにこれらのオブジェクトをグループ化するための Apache Spark Declarative Pipelines（SDP）を学習します。このコースでは、メダリオンアーキテクチャ（ブロンズ → シルバー → ゴールド）に沿って、現実的な小売データセットを使用します。Lakeflow ジョブによるオーケストレーションは、ボーナスモジュールとして提供されています。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-12-18T14:00:00"},"endDate":{"value":"2026-12-18T18:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28882","entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5450"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-lakebase-japanese-5450"}}],"nid":28882,"vid":225705,"title":"Get Started with Lakebase - Japanese","price":"75.00","duration":10800,"body":{"processed":"このはじめようコースでは、Databricks Lakebase を紹介します。Databricks Lakebase は、Databricks Data Intelligence Platform に組み込まれたフルマネージド PostgreSQL サービスであり、運用系（OLTP）ワークロードとアナリティクス系（OLAP）ワークロードをより緊密に統合します。
コースはまず概念的な講義から始まり、OLTP システムと OLAP システムを比較しながら、それぞれのパフォーマンス特性、ストレージモデル、および代表的なユースケースについて説明します。また、データ移動、レイテンシー、アーキテクチャの複雑さなど、トランザクションデータベースとアナリティクスプラットフォームを別々に維持する際に組織が直面する課題についても探索します。
次に、Databricks Lakebase がこれらの課題にどのように対処するかを学びます。Lakebase は PostgreSQL 互換の運用データベースを提供し、Databricks Lakehouse と直接統合することで、運用アプリケーションとアナリティクスを統一されたプラットフォーム上で連携させることを可能にします。
ハンズオンラボでは、以下の内容を実施します。
オートスケーリングコンピュートを使用して Lakebase プロジェクトを作成・探索する
• ブランチ、モニタリング、構成設定を含む Lakebase UI を操作する
• Lakebase SQL Editor を使用してテーブルを作成し、クエリーを実行する
• Lakehouse Federation と外部カタログを使用して Databricks から Lakebase データをクエリーする
• Delta テーブルを Lakebase に同期することでリバース ETL を実行する
• Python から Lakebase に接続し、基本的な CRUD 操作を実行する
これははじめようコースであるため、Lakebase を操作するためのコアコンセプトと基本的なワークフローの理解に重点を置いています。Lakebase 上でフルスケールの本番運用アプリケーションを構築することは、本コースの範囲外となります。
コースの終わりには、Unity Catalog と Databricks Lakehouse を基盤とする単一のガバナンスされたプラットフォーム上で、Lakebase が組織の運用システムとアナリティクスを橋渡しする方法について理解できるようになります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28547","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4604"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4604"}}],"nid":28547,"vid":219107,"title":"Get Started with Databricks Platform Administration - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platformにおけるプラットフォーム管理の基礎を学びます。Databricks環境内での効果的なデータガバナンスに不可欠なコンポーネントであるUnity Catalogの包括的な概要を提供します。5つのモジュールに分かれており、Databricksインフラストラクチャとdata intelligence platformの詳細な紹介から始まります。Databricks workspaceの詳細な操作手順も含まれます。Unity Catalog内のデータガバナンス原則を探求し、その主要な概念、アーキテクチャ、役割をカバーします。さらに、クラスターやSQLウェアハウスを含む、Unity Catalog metastoresとコンピューティングリソースの管理に重点を置きます。最後に、権限、きめ細かいアクセス制御、データオブジェクトのガバナンス手法を学び、データアクセス制御を習得します。修了時には、効果的なデータガバナンスの実装、コンピューティングリソースの最適化、堅牢なデータセキュリティ戦略の徹底に必要な、Unity Catalog管理の必須スキルを身につけます。Databricks Labsサブスクリプションを購入すると、コースの最後には、ライブのDatabricks workspace環境で学んだ内容を実践する包括的なラボ演習が用意されています。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28091","entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4081"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4081"}}],"nid":28091,"vid":217396,"title":"Introduction to Apache Spark™ - Japanese","price":"750.00","duration":14400,"body":{"processed":"この初心者向けコースでは、大規模データ処理のための Apache Spark の基礎を学びます。Spark の分散アーキテクチャを探索し、DataFrame API を習得し、Python を使用してデータの読み込み、書き込み、処理を行う方法を学びます。ハンズオン演習を通じて、Spark の変換処理とアクションを効率的に実行するために必要なスキルを身につけます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-18T09:00:00"},"endDate":{"value":"2026-12-18T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28172","entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4572"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4572"}}],"nid":28172,"vid":217477,"title":"Stream Processing and Analysis with Apache Spark™ - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Apache Spark を使用したストリーム処理と解析の基本について学習します。 ストリーム処理の基礎をしっかりと理解し、Spark 構造化ストリーミング API を使用してアプリケーションを開発します。 ストリーム集約やウィンドウ分析などの高度な手法を探索して、リアルタイム データを効率的に処理します。 このコースでは、動的データ環境向けにスケーラブルでフォールトトレラントなストリーミングアプリケーションを作成するスキルを身に付けます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28292","entityUrl":{"path":"/jp/training/catalog/data-ingestion-with-lakeflow-connect-japanese-2866"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-ingestion-with-lakeflow-connect-japanese-2866"}}],"nid":28292,"vid":217597,"title":"Data Ingestion with Lakeflow Connect - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、幅広いソースからDatabricksへデータを取り込むためのスケーラブルかつシンプルなソリューションであるLakeFlow Connectについて、包括的な入門知識を提供します。まず、LakeFlow Connectのさまざまなコネクタの種類（StandardおよびManaged）を探索し、バッチ、インクリメンタルバッチ、ストリーミングによるデータ取り込みなど、各種データ取り込み手法を学びます。また、Delta テーブルとメダリオンアーキテクチャを使用する主なメリットについても確認します。
次に、LakeFlow Connect Standard Connectorを使用してクラウドオブジェクトストレージからデータを取り込む実践的なスキルを習得します。具体的には、CREATE TABLE AS SELECT（CTAS）、COPY INTO、Auto Loaderといった手法を取り上げ、それぞれのアプローチのメリットと考慮事項を重点的に学びます。また、Databricks Data Intelligence Platformへの取り込み時に、ブロンズレベルのテーブルにメタデータ列を追加する方法についても学習します。続いて、テーブルスキーマに一致しないレコードをrescued dataカラムを使って処理する方法と、そのデータを管理・分析するための戦略を取り上げます。さらに、半構造化されたJSONデータの取り込みとフラット化の手法についても探索します。
その後、LakeFlow Connect Managed Connectorを使用して、データベースやSaaSアプリケーションからエンタープライズグレードのデータ取り込みを実行する方法を探索します。また、Partner Connectを取り込みワークロードにパートナーツールを統合するオプションとして紹介します。
最後に、MERGE INTO 操作やDatabricks Marketplaceの活用を含む代替の取り込み戦略を取り上げ、現代のデータエンジニアリングのユースケースをサポートするための強固な基盤を身に付けます。
注意：Databricks Academyでは、Databricks環境内での教室セッションにおいて、ノートブックベースの形式への移行を進めており、講義でのスライドデッキの使用を廃止しています。講義ノートブックはVocareumのラボ環境からアクセスできます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-13T14:00:00"},"endDate":{"value":"2026-10-13T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-26T09:00:00"},"endDate":{"value":"2027-01-26T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28391","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3568"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3568"}}],"nid":28391,"vid":217696,"title":"Get Started with Databricks for Machine Learning - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Data Intelligence Platformを使用して基本的な機械学習workflowsを実行し、データサイエンスワークロードをサポートするために必要な基礎スキルを習得します。機械学習実践者の視点からプラットフォームを探求し、Databricks Notebooks による特徴量エンジニアリングや MLflow によるモデルライフサイクル追跡などのトピックをカバーします。さらに、Mosaic AI Model Serving によるリアルタイムモデル推論について学び、AutoML を通じて Databricks の「ガラス箱」アプローチによるモデル開発を体験します。本コースには講師主導のデモが 3 回含まれており、デモで学んだ概念を強化する包括的なラボで締めくくられます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28092","entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4084"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4084"}}],"nid":28092,"vid":217397,"title":"Stream Processing and Analysis with Apache Spark - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks 上で Spark 構造化ストリーミング API を使用して、スケーラブルでフォールトトレラントなストリーム処理アプリケーションを開発する方法を学習者に解説します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-04T09:00:00"},"endDate":{"value":"2026-12-04T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28173","entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4574"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/stream-processing-and-analysis-with-apache-spark-japanese-4574"}}],"nid":28173,"vid":217478,"title":"Stream Processing and Analysis with Apache Spark™ - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Apache Spark を使用したストリーム処理と解析の基本について学習します。 ストリーム処理の基礎をしっかりと理解し、Spark 構造化ストリーミング API を使用してアプリケーションを開発します。 ストリーム集約やウィンドウ分析などの高度な手法を探索して、リアルタイム データを効率的に処理します。 このコースでは、動的データ環境向けにスケーラブルでフォールトトレラントなストリーミングアプリケーションを作成するスキルを身に付けます。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28295","entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-japanese-2872"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-japanese-2872"}}],"nid":28295,"vid":217600,"title":"Build Data Pipelines with Apache Spark™ Declarative Pipelines - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks の Apache Spark™ Declarative Pipelines (SDP) を使用して、インクリメンタルなバッチまたはストリーミングの取り込みと処理を複数のストリーミングテーブルおよびマテリアライズドビューを通じて実行するデータパイプラインを構築するために必要な基本的な概念とスキルをユーザーに紹介します。Spark Declarative Pipelines を初めて使用するデータエンジニアを対象として設計されたこのコースでは、インクリメンタルデータ処理、ストリーミングテーブル、マテリアライズドビュー、一時ビューなどのコアコンポーネントについて包括的な概要を提供し、それぞれの目的と違いを明確に説明します。
カバーするトピックは以下のとおりです：
• SQL を使用した Spark Declarative Pipelines のマルチファイルエディターによる ETL パイプラインの開発とデバッグ（Python コード例も提供）
• Spark Declarative Pipelines がパイプライングラフを通じてパイプライン内のデータ依存関係を追跡する方法
• パイプラインのコンピュートリソース、データアセット、トリガーモード、その他の詳細オプションの設定
次に、このコースでは Spark Declarative Pipelines におけるデータ品質エクスペクテーションを紹介し、データ完全性を検証・強制するためにエクスペクテーションをパイプラインに統合するプロセスをユーザーに案内します。その後、スケジューリングオプションやパイプラインのパフォーマンスと健全性を監視するためのパイプラインイベントロギングの有効化など、パイプラインを本番運用に移行する方法を探索します。
最後に、このコースでは Spark Declarative Pipelines 内の AUTO CDC INTO 構文を使用してチェンジデータキャプチャ (CDC) を実装し、slowly changing dimensions（SCD Type 1 および Type 2）を管理する方法を説明し、ユーザーが CDC を自身のパイプラインに統合できるよう準備します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-19T14:00:00"},"endDate":{"value":"2026-10-19T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-16T09:00:00"},"endDate":{"value":"2026-12-16T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28392","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3569"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3569"}}],"nid":28392,"vid":217697,"title":"Get Started with Databricks for Machine Learning - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platformを使用して基本的な機械学習workflowsを実行し、データサイエンスワークロードをサポートするために必要な基礎スキルを習得します。機械学習実践者の視点からプラットフォームを探求し、Databricks Notebooks による特徴量エンジニアリングや MLflow によるモデルライフサイクル追跡などのトピックをカバーします。さらに、Mosaic AI Model Serving によるリアルタイムモデル推論について学び、AutoML を通じて Databricks の「ガラス箱」アプローチによるモデル開発を体験します。本コースには講師主導のデモが 3 回含まれており、デモで学んだ概念を強化する包括的なラボで締めくくられます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28094","entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4094"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4094"}}],"nid":28094,"vid":217399,"title":"SQL Analytics on Databricks - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、特に Databricks SQL に焦点を当てて、データ分析に Databricks を効果的に使用する方法を学習します。 Databricks データアナリストの責任には、関連データの検索、潜在的なアプリケーションのための分析、貴重なビジネスインサイトを提供する形式への変換が含まれます。
また、データオブジェクトの管理における自分の役割と、ノートブック、SQL エディター、Databricks SQL などのツールを使用して Databricks データインテリジェンスプラットフォーム内でデータオブジェクトを操作する方法についても理解できます。
さらに、データ資産とプラットフォーム全体の管理における Unity Catalog の重要性についても学習します。 最後に、このコースでは、Databricksがパフォーマンスの最適化を促進する方法の概要を説明し、クエリーインサイトにアクセスして、DatabricksでSQLアナリティクスを実行するときにバックグラウンドで発生するプロセスを理解する方法について説明します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28187","entityUrl":{"path":"/jp/training/catalog/databricks-accredited-platform-administrator-accreditation-japanese-4660"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-accredited-platform-administrator-accreditation-japanese-4660"}}],"nid":28187,"vid":217492,"title":"Databricks Accredited Platform Administrator Accreditation - Japanese","price":"0.00","duration":1200,"body":{"processed":"Databricks認定プラットフォーム管理者試験は、20分間の無監督認定試験であり、Unity Catalogを使用したDatabricks Lakehouse Platformの管理および運用に関する知識を評価します。本試験では、プラットフォーム管理の基本操作、ID管理、プラットフォームの設定とセキュリティ対策、コンピューティングリソースの管理、プラットフォーム内データの管理とセキュリティ対策、プラットフォーム内CI/CDツールの管理に関する能力を評価します。試験に合格した受験者には、Databricks認定プラットフォーム管理者バッジと認定証が授与されます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28298","entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-2878"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/deploy-workloads-with-lakeflow-jobs-japanese-2878"}}],"nid":28298,"vid":217603,"title":"Deploy Workloads with Lakeflow Jobs - Japanese","price":"750.00","duration":14400,"body":{"processed":"Deploy Workloads with Lakeflow Jobs コースでは、Databricks エコシステム内の統合オーケストレーションプラットフォームとして Lakeflow Jobs を使用し、データ、アナリティクス、および AI ワークフローをオーケストレーションおよび自動化する方法を学びます。
• 有向非環状グラフ（DAG）を使用したデータワークロードの設計と実装、各種スケジューリングオプションの設定、および条件付きタスク実行、run-if 依存関係、for each ループなどの高度なワークフロー機能の実装について学習します。
• 本コースでは、適切なコンピュート選択、モジュール式オーケストレーション、エラー処理技術、およびフォールトトレラント設計を備えた、堅牢で本番運用に対応したパイプラインを作成するためのベストプラクティスを取り上げます。これらはすべて Databricks Data Intelligence Platform 内にネイティブに統合されています。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-15T14:00:00"},"endDate":{"value":"2026-10-15T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-22T09:00:00"},"endDate":{"value":"2027-01-22T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28405","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3665"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-generative-ai-japanese-3665"}}],"nid":28405,"vid":217710,"title":"Get Started with Databricks for Generative AI - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform の実践的な入門として、Generative AI システムの構築およびデプロイに向けたキーコンポーネントと機能を中心に学習します。参加者は、Databricks がスケーラブルな Generative AI ソリューションの開発をどのように支援するかを学び、AI Search、Agent Framework、およびモデルのトラッキングとロギングのための MLflow の Generative AI 機能などのツールを探索します。このコースでは、Retrieval-Augmented Generation (RAG) パイプラインの構築と評価、Generative AI エージェントのデプロイ、およびパフォーマンスを最適化するための評価 Framework の活用について、ハンズオン形式で学ぶ機会が含まれています。コース修了時には、学習者は Databricks Data Intelligence Platform 上で一般的な Generative AI アプリケーションを設計、デプロイ、および監視するためのスキルを身につけることができます。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"28097","entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4120"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4120"}}],"nid":28097,"vid":217402,"title":"SQL Analytics on Databricks - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、特に Databricks SQL に焦点を当てて、データ分析に Databricks を効果的に使用する方法を学習します。 Databricks データアナリストの責任には、関連データの検索、潜在的なアプリケーションのための分析、貴重なビジネスインサイトを提供する形式への変換が含まれます。
また、データオブジェクトの管理における自分の役割と、ノートブック、SQL エディター、Databricks SQL などのツールを使用して Databricks データインテリジェンスプラットフォーム内でデータオブジェクトを操作する方法についても理解できます。
さらに、データ資産とプラットフォーム全体の管理における Unity Catalog の重要性についても学習します。 最後に、このコースでは、Databricksがパフォーマンスの最適化を促進する方法の概要を説明し、クエリーインサイトにアクセスして、DatabricksでSQLアナリティクスを実行するときにバックグラウンドで発生するプロセスを理解する方法について説明します。
Languages Available: English | 日本語 | Português BR | 한국어
このコースでは、Databricks Data Intelligence Platformのプラットフォーム管理の基礎を学習します。 Databricksアーキテクチャ、セキュリティモデル、管理者の役割、クラウドリソース管理、および自動化手法について説明します。 Workspaces、Metastores、外部ストレージの管理など、主要な管理責任を探りながら、アクセス制御とロールベースの権限によってセキュリティを確保します。 さらに、Databricks SDK, CLI,とTerraformを使用して管理タスクを自動化する方法を学習します。 このコースには、概念を強化し、プラットフォーム管理を合理化するための実践的なデモンストレーションが含まれています。 最終的には、組織内の Databricks 環境を効率的に管理、保護、自動化できるようになります。
Databricks を使用したデータエンジニアリングを学ぶための適切な入門コースです。
以下では、このコースに含まれる 4 つの 4 時間モジュールについてそれぞれ説明します。
注: 以下の 4 つのモジュールについて、Databricks Academy は Databricks 環境内での教室セッションを notebook ベースの形式に移行しており、講義でのスライドデッキの使用を終了します。講義用 notebook には Vocareum lab 環境でアクセスできます。
1. Data Ingestion with Lakeflow Connect
このコースでは、幅広いソースから Databricks へデータを取り込むための、スケーラブルで簡素化されたソリューションである Lakeflow Connect について包括的に紹介します。まず、Lakeflow Connect コネクタのさまざまな種類（Standard および Managed）を確認し、バッチ、増分バッチ、ストリーミングによる取り込みなど、多様なデータ取り込み手法を学びます。また、Delta table と Medallion アーキテクチャを使用する主な利点についても復習します。
次に、Lakeflow Connect Standard Connectors を使用して、クラウドオブジェクトストレージからデータを取り込むための実践的なスキルを習得します。これには、CREATE TABLE AS SELECT (CTAS)、COPY INTO、Auto Loader などの手法の活用が含まれ、各アプローチの利点と考慮事項に重点を置きます。また、Databricks Data Intelligence Platform への取り込み時に、bronze レベルのテーブルにメタデータ列を追加する方法も学びます。続いて、rescued data 列を使用してテーブルスキーマに一致しないレコードを処理する方法や、このデータを管理・分析するための戦略について取り上げます。さらに、半構造化 JSON データを取り込んでフラット化する手法についても確認します。
その後、Lakeflow Connect Managed Connectors を使用して、データベースや Software-as-a-Service (SaaS) アプリケーションからデータを取り込む、エンタープライズグレードのデータ取り込みを実行する方法を確認します。また、パートナーツールを取り込みワークロードに統合するためのオプションとして Partner Connect も紹介します。
最後に、MERGE INTO 操作や Databricks Marketplace の活用など、代替の取り込み戦略を取り上げ、最新のデータエンジニアリングのユースケースを支える確かな基盤を身に付けます。
2. Deploy Workloads with Lakeflow Jobs
Deploy Workloads with Lakeflow Jobs コースでは、Databricks エコシステム内の統合オーケストレーションプラットフォームである Lakeflow Jobs を使用して、データ、分析、AI のワークフローをオーケストレーションおよび自動化する方法を学びます。
• 有向非巡回グラフ (DAG) を使用してデータワークロードを設計・実装し、さまざまなスケジューリングオプションを構成し、条件付きタスク実行、run-if 依存関係、for each ループなどの高度なワークフロー機能を実装する方法を学びます。
• このコースでは、適切なコンピュートの選択、モジュール式のオーケストレーション、エラー処理手法、フォールトトレラントな設計を備えた、堅牢で本番環境対応のパイプラインを作成するためのベストプラクティスを取り上げます。これらはすべて Databricks Data Intelligence Platform にネイティブに統合されています。
3. Build Data Pipelines with Apache Spark Declarative Pipelines
このコースでは、Databricks の Apache Spark Declarative Pipelines (SDP) を使用して、複数のストリーミングテーブルとマテリアライズドビューを通じた増分バッチまたはストリーミングの取り込みと処理を行うデータパイプラインを構築するために必要な、基本的な概念とスキルを紹介します。Spark Declarative Pipelines を初めて使用するデータエンジニア向けに設計されており、増分データ処理、ストリーミングテーブル、マテリアライズドビュー、一時ビューなどの主要コンポーネントを包括的に概説し、それぞれの目的と違いを明確にします。
取り上げるトピックは以下のとおりです。
• SQL を使用した Spark Declarative Pipelines のマルチファイルエディタによる ETL パイプラインの開発とデバッグ（Python コード例を提供）
• Spark Declarative Pipelines がパイプライングラフを通じてパイプライン内のデータ依存関係を追跡する方法
• パイプラインのコンピュートリソース、データアセット、トリガーモード、その他の高度なオプションの構成
次に、Spark Declarative Pipelines のデータ品質エクスペクテーションを紹介し、データの整合性を検証・強制するためにエクスペクテーションをパイプラインに統合するプロセスを案内します。続いて、スケジューリングオプションを含むパイプラインの本番稼働の方法や、パイプラインのパフォーマンスと正常性を監視するためのパイプラインイベントログの有効化について確認します。
最後に、Spark Declarative Pipelines 内で AUTO CDC INTO 構文を使用して Change Data Capture (CDC) を実装し、緩やかに変化するディメンション（SCD Type 1 および Type 2）を管理する方法を取り上げ、CDC を自身のパイプラインに統合できるように準備します。
4. DevOps Essentials for Data Engineering
このコースでは、Databricks を使用するデータエンジニア向けに特化した、ソフトウェアエンジニアリングのベストプラクティスと DevOps の原則を探求します。受講者は、コード品質、バージョン管理、ドキュメント作成、テストといった主要トピックについて確かな基盤を築きます。このコースでは DevOps に重点を置き、その中核となるコンポーネント、利点、そしてデータエンジニアリングのワークフローを最適化する上での継続的インテグレーションとデリバリー (CI/CD) の役割を取り上げます。
再利用可能なコンポーネントを作成し、コードを効率的に構造化するために、PySpark でモジュール性の原則を適用する方法を学びます。ハンズオンでは、pytest フレームワークを使用した PySpark 関数の単体テストの設計と実装、続いて信頼性を確保するための Spark Declarative Pipeline および Jobs を使用した Databricks データパイプラインの統合テストを行います。
また、継続的インテグレーションのプラクティスを統合するための Databricks Git Folders の使用など、Databricks 内の必須の Git 操作についても取り上げます。最後に、REST API、CLI、SDK、Declarative Automation Bundles (DABs) など、Databricks アセットのさまざまなデプロイ方法を大まかに確認し、パイプラインをデプロイ・管理するための手法に関する知識を習得します。
コースを修了する頃には、ソフトウェアエンジニアリングと DevOps のベストプラクティスに習熟し、スケーラブルで保守性が高く、効率的なデータエンジニアリングソリューションを構築できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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PySpark でモジュール性の原則を適用する方法を学び、再利用可能なコンポーネントを作成してコードを効率的に構造化します。ハンズオン演習では、pytest Framework を使用した PySpark 関数のユニットテストの設計と実装、続いて Spark Declarative Pipeline と Jobs を使用した Databricks データパイプラインのインテグレーションテストを通じて、信頼性を確保します。
また、Databricks Git Folders を使用した継続的インテグレーションプラクティスの統合など、Databricks 内での重要な Git 操作についても学びます。最後に、REST API、CLI、SDK、および Declarative Automation Bundles（DABs）など、Databricks アセットのさまざまなデプロイメント方法を概観し、パイプラインをデプロイおよび管理するための技術的な知識を習得します。
コース修了時には、ソフトウェアエンジニアリングと DevOps のベストプラクティスを習得し、スケーラブルで保守性が高く効率的なデータエンジニアリングソリューションを構築できるようになります。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-21T14:00:00"},"endDate":{"value":"2026-10-21T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-18T09:00:00"},"endDate":{"value":"2026-12-18T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28099","entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4184"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4184"}}],"nid":28099,"vid":217404,"title":"Data Modeling Strategies - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks Lakehouse Platformを使用して、スケーラブルで分析に対応したデータモデルを設計する方法を学習します。 このコースは3つのモジュールで構成されており、基本的なデータモデリングの原則、高度なウェアハウジングと機械学習のユースケース、最新のデータ製品設計をカバーしています。 Inmon の CIF、Kimball のディメンションモデリング、Data Vault 2.0 などの主要な方法論と、これらの戦略を Databricks に実装するための実践的なデモを紹介します。
ハンズオン ラボでは、ER 図を作成し、SCD タイプ 2 変換を適用し、ML ワークフロー用の Feature Store を作成します。 また、データ製品の概念と、製品の考え方、ガバナンス、セマンティックの一貫性によってスケーラブルなクロスドメイン統合がどのように可能になるかについても紹介します。 このコースを修了すると、統合されたレイクハウスアーキテクチャでデータを効果的にモデル化、管理、運用できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-19T09:00:00"},"endDate":{"value":"2026-10-19T13:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-20T09:00:00"},"endDate":{"value":"2027-01-20T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28201","entityUrl":{"path":"/jp/training/catalog/ai-agent-fundamentals-japanese-4748"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/ai-agent-fundamentals-japanese-4748"}}],"nid":28201,"vid":217506,"title":"AI Agent Fundamentals - Japanese","price":"0.00","duration":5400,"body":{"processed":"このファンデーショナルコースでは、AI エージェントと、Mosaic AI プラットフォームおよび Agent Bricks を含む Databricks 上のエンタープライズアプリケーションにおけるその活用方法を紹介します。学習者は、AI エージェントとは何か、どのように機能するか、そして複雑なタスクを処理するために人間の推論をどのように模倣するかについて学びます。
本コースでは、エージェントの実際のユースケースを取り上げ、エージェンティックワークフローやマルチエージェントシステムなどの高度なトピックについて基本的な概要を提供します。また、Agent Bricks がさまざまなアプリケーションにわたってエンタープライズ対応エージェントの開発をどのように簡素化するかを探り、Databricks 上でエージェントを構築・活用する方法を示すデモも含まれています。
Languages Available: English | 日本語 | Português BR | 한국어
このコースでは、SparkとDelta Lakeを用いたワークロードと物理レイアウトの最適化手法、およびSpark UIの分析によるパフォーマンス評価とアプリケーションのデバッグ方法を学びます。ストリーミング、流動的クラスタリング、データスキップ、キャッシュ、Photonsなどのトピックを網羅します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-26T13:00:00"},"endDate":{"value":"2026-10-26T17:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-25T09:00:00"},"endDate":{"value":"2027-01-25T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28440","entityUrl":{"path":"/jp/training/catalog/automated-deployment-with-declarative-automation-bundles-japanese-3913"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/automated-deployment-with-declarative-automation-bundles-japanese-3913"}}],"nid":28440,"vid":217745,"title":"Automated Deployment with Declarative Automation Bundles - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、DevOps の原則と Databricks プロジェクトへの適用について包括的に学習します。まず、DevOps、DataOps、継続的インテグレーション（CI）、継続的デプロイメント（CD）、およびテストの中核となる概念の概要を説明し、これらの原則をデータエンジニアリングパイプラインに適用する方法を探ります。
次に、CI/CD プロセスにおける継続的デプロイメントに焦点を当て、プロジェクトのデプロイメントに使用する Databricks REST API、SDK、CLI などのツールについて説明します。Declarative Automation Bundles（DABs）の概念と、CI/CD プロセスにおける位置づけを学びます。DABs の主要なコンポーネント、フォルダー構造、および Databricks のさまざまなターゲット環境へのデプロイメントを効率化する方法について詳しく解説します。また、Databricks CLI を使用して、異なる構成を持つ複数の環境向けに Declarative Automation Bundles に変数を追加し、変更、検証、デプロイ、および実行する方法についても学習します。
最後に、Declarative Automation Bundles をローカルで構築、テスト、およびデプロイするためのインタラクティブ開発環境（IDE）として Visual Studio Code を紹介し、開発プロセスの最適化を図ります。コースの締めくくりとして、GitHub Actions を使用してデプロイメントパイプラインを自動化し、Declarative Automation Bundles を活用した CI/CD ワークフローを強化する方法を紹介します。
このコースを修了すると、DevOps プラクティスを通じて効率性を向上させながら、Declarative Automation Bundles を使用して Databricks プロジェクトのデプロイメントを自動化できるようになります。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-28T13:00:00"},"endDate":{"value":"2026-10-28T17:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-29T09:00:00"},"endDate":{"value":"2027-01-29T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28112","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-4210"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-warehousing-japanese-4210"}}],"nid":28112,"vid":217417,"title":"Get Started with Databricks for Data Warehousing - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks のモダンなデータウェアハウジングアプローチについて、包括的かつハンズオン形式で概説します。データレイクハウスアーキテクチャが、従来のデータウェアハウスの強みとクラウドの柔軟性・スケーラビリティをどのように組み合わせているかを重点的に取り上げます。架空の小売業者（Vintage Audio Co.）を題材にエンドツーエンドで作業しながら、ワークスペースの探索、ガバナンスされた Unity Catalog テーブルへのクエリー、分析読み取りを高速に保つための Unity Catalog マネージドテーブルの最適化、Auto Loader を使ったインクリメンタルなデータ読み込み、スタースキーマのモデリング、そして Unity Catalog メトリクスビューを通じた一貫した知見の提供まで、すべてを単一のガバナンスされた環境から実施します。さらに、AI 駆動の機能（Predictive Optimization、Genie Code）が全体を通じて組み込まれています。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
Languages Available: English | 日本語 | Português BR| 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"28205","entityUrl":{"path":"/jp/training/catalog/get-started-with-ai-agents-on-databricks-japanese-4788"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-ai-agents-on-databricks-japanese-4788"}}],"nid":28205,"vid":217510,"title":"Get Started with AI Agents on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、AIエージェント、最新のAIアプリケーションにおけるAIエージェントの役割、およびDatabricks PlatformでAIエージェントアプリケーションを構築する方法を紹介します。 AI エージェントの原則、従来の AI システムとの違いについて学び、キー コンポーネントについて説明します。 インタラクティブなデモとハンズオンラボを通じて、Mosaic AI とエージェントブリックを使用して AI エージェントを Databricks で構築、デプロイ、評価する方法を確認できます。 このコースを修了すると、Databricks Data Intelligence Platform を使用して AI エージェントを作成およびデプロイする方法を理解できます.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28317","entityUrl":{"path":"/jp/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-japanese-3028"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-japanese-3028"}}],"nid":28317,"vid":217622,"title":"Advanced Techniques with Apache Spark Declarative Pipelines - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、本番運用グレードのストリーミングパイプラインを構築するための Databricks の Apache Spark Declarative Pipelines (SDP) について学びます。実際の Lakehouse エンジニアリングに不可欠な高度なデザインパターン、堅牢なデータ品質の適用、およびクロスプラットフォーム統合を習得します。
コース全体を通じて、最新のデータ取り込みおよび処理技術を深く学び、レイアウト最適化のためのリキッドクラスタリングや、混在スキーマイベントに対応するマルチプレックスストリーミングパターンなどのツールを習得します。モジュールの終わりには、スキーマ進化を自信を持って処理し、チェンジデータキャプチャ (CDC) を自動化し、データ完全性を確保する方法を習得できます。
講義とハンズオンデモを通じて、以下のことを学びます。
• 複数ソースのデータを統合されたブロンズテーブルに取り込むマルチフローパイプラインを構築する。
• シルバーおよびゴールドレイヤー全体にリキッドクラスタリングとデータ品質 Expectations を適用する。
• クロスプラットフォームのデータアクセスのために Iceberg UniForm を使用したマルチプレックスパターンを実装する。
• AUTO CDC INTO を使用して SCD Type 2 の履歴トラッキングを自動化する。
• 無効なレコードを監査・管理するためのゼロデータロス隔離パイプラインを設計する。
注意：Databricks Academyでは、Databricks環境内でのクラスルームセッションをノートブックベースのフォーマットに移行しており、スライドデッキを用いた講義は廃止されます。講義用ノートブックには、Vocareumラボ環境からアクセスできます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-27T14:00:00"},"endDate":{"value":"2026-10-27T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-01T09:00:00"},"endDate":{"value":"2026-12-01T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28442","entityUrl":{"path":"/jp/training/catalog/devops-essentials-for-data-engineering-japanese-3919"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/devops-essentials-for-data-engineering-japanese-3919"}}],"nid":28442,"vid":217747,"title":"DevOps Essentials for Data Engineering - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks を使用するデータエンジニア向けに特別に設計された、ソフトウェアエンジニアリングのベストプラクティスと DevOps の原則について説明します。 参加者は、コード品質、バージョン管理、ドキュメンテーション、テストなどの主要なトピックで強力な基盤を構築します。 このコースではDevOpsに重点を置き、コアコンポーネント、利点、およびデータエンジニアリングワークフローの最適化における継続的インテグレーションと継続的デリバリー(CI/CD)の役割について説明します
PySpark でモジュール性の原則を適用して、再利用可能なコンポーネントを作成し、コードを効率的に構造化する方法を学習します。 実践的な経験には、pytest フレームワークを使用した PySpark 関数の単体テストの設計と実装、その後の DLT と Workflows を使用した Databricks データパイプラインの統合テストが含まれ、信頼性を確保します
このコースでは、Databricks Git フォルダーを使用した継続的インテグレーションのプラクティスの統合など、Databricks 内の基本的な Git 操作についても説明します。 最後に、REST API、CLI、SDK、Databricks アセットバンドル (DAB) など、Databricks アセットのさまざまなデプロイ方法の概要を説明し、パイプラインをデプロイして管理する手法に関する知識を身に付けます
このコースを修了すると、ソフトウェアエンジニアリングとDevOpsのベストプラクティスに習熟し、スケーラブルで保守可能、かつ効率的なデータエンジニアリングソリューションを構築できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28113","entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4211"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/sql-analytics-on-databricks-japanese-4211"}}],"nid":28113,"vid":217418,"title":"SQL Analytics on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、特に Databricks SQL に焦点を当てて、データ分析に Databricks を効果的に使用する方法を学習します。 Databricks データアナリストの責任には、関連データの検索、潜在的なアプリケーションのための分析、貴重なビジネスインサイトを提供する形式への変換が含まれます。
また、データオブジェクトの管理における自分の役割と、ノートブック、SQL エディター、Databricks SQL などのツールを使用して Databricks データインテリジェンスプラットフォーム内でデータオブジェクトを操作する方法についても理解できます。
さらに、データ資産とプラットフォーム全体の管理における Unity Catalog の重要性についても学習します。 最後に、このコースでは、Databricksがパフォーマンスの最適化を促進する方法の概要を説明し、クエリーインサイトにアクセスして、DatabricksでSQLアナリティクスを実行するときにバックグラウンドで発生するプロセスを理解する方法について説明します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28208","entityUrl":{"path":"/jp/training/catalog/data-governance-fundamentals-japanese-4819"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-governance-fundamentals-japanese-4819"}}],"nid":28208,"vid":217513,"title":"Data Governance Fundamentals - Japanese","price":"0.00","duration":2700,"body":{"processed":"このコースでは、データガバナンスとUnity Catalogの基礎を探ります。 データカタログの進化と目的、Unity Catalogのアーキテクチャとコンポーネント、ガバナンスにおけるデータ品質、セキュリティ、コンプライアンス、リネージ、監査の重要性について学習します。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28322","entityUrl":{"path":"/jp/training/catalog/databricks-performance-optimization-japanese-3079"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-performance-optimization-japanese-3079"}}],"nid":28322,"vid":217627,"title":"Databricks Performance Optimization - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、SparkとDelta Lakeを用いたワークロードと物理レイアウトの最適化手法、およびSpark UIの分析によるパフォーマンス評価とアプリケーションのデバッグ方法を学びます。ストリーミング、流動的クラスタリング、データスキップ、キャッシュ、Photonsなどのトピックを網羅します。
注記：このコースは「Advanced Data Engineering with Databricks」コースの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28443","entityUrl":{"path":"/jp/training/catalog/devops-essentials-for-data-engineering-japanese-3920"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/devops-essentials-for-data-engineering-japanese-3920"}}],"nid":28443,"vid":217748,"title":"DevOps Essentials for Data Engineering - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks を使用するデータエンジニア向けに特別に設計された、ソフトウェアエンジニアリングのベストプラクティスと DevOps の原則について説明します。 参加者は、コード品質、バージョン管理、ドキュメンテーション、テストなどの主要なトピックで強力な基盤を構築します。 このコースではDevOpsに重点を置き、コアコンポーネント、利点、およびデータエンジニアリングワークフローの最適化における継続的インテグレーションと継続的デリバリー(CI/CD)の役割について説明します
PySpark でモジュール性の原則を適用して、再利用可能なコンポーネントを作成し、コードを効率的に構造化する方法を学習します。 実践的な経験には、pytest フレームワークを使用した PySpark 関数の単体テストの設計と実装、その後の DLT と Workflows を使用した Databricks データパイプラインの統合テストが含まれ、信頼性を確保します
このコースでは、Databricks Git フォルダーを使用した継続的インテグレーションのプラクティスの統合など、Databricks 内の基本的な Git 操作についても説明します。 最後に、REST API、CLI、SDK、Databricks アセットバンドル (DAB) など、Databricks アセットのさまざまなデプロイ方法の概要を説明し、パイプラインをデプロイして管理する手法に関する知識を身に付けます
このコースを修了すると、ソフトウェアエンジニアリングとDevOpsのベストプラクティスに習熟し、スケーラブルで保守可能、かつ効率的なデータエンジニアリングソリューションを構築できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28130","entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4273"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4273"}}],"nid":28130,"vid":217435,"title":"Data Modeling Strategies - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Lakehouse Platformを使用して、スケーラブルで分析に対応したデータモデルを設計する方法を学習します。 このコースは3つのモジュールで構成されており、基本的なデータモデリングの原則、高度なウェアハウジングと機械学習のユースケース、最新のデータ製品設計をカバーしています。 Inmon の CIF、Kimball のディメンションモデリング、Data Vault 2.0 などの主要な方法論と、これらの戦略を Databricks に実装するための実践的なデモを紹介します。
ハンズオン ラボでは、ER 図を作成し、SCD タイプ 2 変換を適用し、ML ワークフロー用の Feature Store を作成します。 また、データ製品の概念と、製品の考え方、ガバナンス、セマンティックの一貫性によってスケーラブルなクロスドメイン統合がどのように可能になるかについても紹介します。 このコースを修了すると、統合されたレイクハウスアーキテクチャでデータを効果的にモデル化、管理、運用できるようになります。
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28210","entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4829"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4829"}}],"nid":28210,"vid":217515,"title":"Get Started with Data Governance on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、ハンズオンデモとキャップストーンラボを通じて、Databricks 上の Unity Catalog ときめ細かいアクセス制御を探索します。テーブルの種類、カタログとスキーマの設定、グループベースのアクセス管理、およびアクセス制御の移行戦略について学習します。このコースには、行レベルセキュリティと列マスキングによるきめ細かいアクセス制御の適用、属性ベースのアクセス制御、制御の組み合わせ、制御の移行に関するデモ、および包括的なガバナンス実装のためのラボが含まれています。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28325","entityUrl":{"path":"/jp/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-japanese-3082"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-japanese-3082"}}],"nid":28325,"vid":217630,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Japanese","price":"0.00","duration":14400,"body":{"processed":"このコースでは、計算モデル、ストリーミング読み取りの構成、ストリーミング環境でのデータ品質の維持など、Spark 構造化ストリーミングとDelta Lakeの包括的な理解を提供します。
注記：このコースは「Advanced Data Engineering with Databricks」コースの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28476","entityUrl":{"path":"/jp/training/catalog/generative-ai-fundamentals-accreditation-japanese-2311"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/generative-ai-fundamentals-accreditation-japanese-2311"}}],"nid":28476,"vid":217781,"title":"Generative AI Fundamentals Accreditation - Japanese","price":"0.00","duration":900,"body":{"processed":"これは、Generative AI に関連する基本概念に関する知識をテストする 20 分間の評価です。
この評価を正常に完了すると、Databricks Generative AI Fundamentals バッジが付与されます。
Languages Available: English | 日本語 | Português BR | 한국어 | Français
このコースでは、DevOpsの原則とDatabricks projectへの応用について包括的に解説します。まず、DevOps、DataOps、継続的インテグレーション（CI）、継続的デプロイメント（CD）、テストといった中核概念の概要から始め、これらの原則をデータエンジニアリングパイプラインに適用する方法を探求します。
コースでは次に、CI/CDプロセス内での継続的デプロイに焦点を当て、プロジェクトデプロイのためのDatabricks REST API、SDK、CLIなどのツールを検証します。Databricks Asset Bundles（DAB）について学び、それらがCI/CDプロセスにどのように組み込まれるかを理解します。DABの主要コンポーネント、フォルダ構造、Databricks内の様々なターゲット環境へのデプロイを効率化する仕組みについて深く掘り下げます。さらに、Databricks CLIを使用して、異なる構成を持つ複数環境向けにDatabricks Asset Bundlesの変数追加、修正、検証、デプロイ、実行を行う方法も学びます。
最後に、本コースではVisual Studio Codeをインタラクティブ開発環境（IDE）として紹介し、Databricks Asset Bundlesのローカル環境でのビルド、テスト、デプロイを可能にすることで開発プロセスを最適化します。コースの締めくくりとして、GitHub Actionsを用いたデプロイパイプラインの自動化を紹介し、Databricks Asset Bundlesを用いたCI/CDワークフローの強化を図ります。
本コース修了時には、Databricks Asset Bundles を使用して Databricks projectのデプロイを自動化し、DevOps プラクティスを通じて効率性を向上させるスキルを身につけることができます。
注：このコースは「Databricksによる高度なデータエンジニアリング」シリーズの4回目です。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28131","entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4274"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-modeling-strategies-japanese-4274"}}],"nid":28131,"vid":217436,"title":"Data Modeling Strategies - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、Databricks Lakehouse Platformを使用して、スケーラブルで分析に対応したデータモデルを設計する方法を学習します。 このコースは3つのモジュールで構成されており、基本的なデータモデリングの原則、高度なウェアハウジングと機械学習のユースケース、最新のデータ製品設計をカバーしています。 Inmon の CIF、Kimball のディメンションモデリング、Data Vault 2.0 などの主要な方法論と、これらの戦略を Databricks に実装するための実践的なデモを紹介します。
ハンズオン ラボでは、ER 図を作成し、SCD タイプ 2 変換を適用し、ML ワークフロー用の Feature Store を作成します。 また、データ製品の概念と、製品の考え方、ガバナンス、セマンティックの一貫性によってスケーラブルなクロスドメイン統合がどのように可能になるかについても紹介します。 このコースを修了すると、統合されたレイクハウスアーキテクチャでデータを効果的にモデル化、管理、運用できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28213","entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4835"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4835"}}],"nid":28213,"vid":217518,"title":"Get Started with Data Governance on Databricks - Japanese","price":"0.00","duration":10800,"body":{"processed":"このコースでは、ハンズオンデモとキャップストーンラボを使用して、Unity Catalog および Databricks でのきめ細かなアクセス制御について説明します。 テーブルの種類、カタログとスキーマの構成、グループベースのアクセス管理、およびアクセス制御の移行戦略について学習します。 このコースには、行レベルのセキュリティと列マスキングによるきめ細かなアクセス制御の適用、属性ベースのアクセス制御、制御の組み合わせ、制御の移行、および包括的なガバナンス実装のためのラボに関するデモが含まれています。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28336","entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-japanese-3284"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-japanese-3284"}}],"nid":28336,"vid":217641,"title":"Build Data Pipelines with Lakeflow Declarative Pipelines - Japanese","price":"0.00","duration":14400,"body":{"processed":"このコースでは、複数のストリーミングテーブルとマテリアライズドビューを介した増分バッチまたはストリーミング取り込みと処理のために、DatabricksのLakeflow宣言型パイプラインを使用してデータパイプラインを構築するために必要な基本的な概念とスキルをユーザーに紹介します。 このコースは、Lakeflow 宣言的パイプライン を初めて使用するデータエンジニア向けに設計されており、増分データ処理、ストリーミングテーブル、マテリアライズドビュー、一時ビューなどのコアコンポーネントの概要を包括的に説明し、それらの特定の目的と違いを強調します
取り上げるトピックは次のとおりです:
- SQL を使用した Lakeflow のマルチファイル エディターを使用した ETL パイプラインの開発とデバッグ (Python コード例を提供)
- Lakeflow 宣言的パイプライン が パイプライン グラフを通じて パイプライン でデータの依存関係を追跡する方法
- パイプライン コンピュート リソース、データ アセット、トリガー モード、およびその他の詳細オプションの構成
次に、このコースでは、Lakeflow のデータ品質に対する期待値を紹介し、データの整合性を検証および適用するために、期待値をパイプラインに統合するプロセスをユーザーに案内します。 次に、学習者は、スケジュール オプション、本番運用モード、パイプラインのパフォーマンスと正常性を監視するためのパイプライン イベント ログの有効化など、パイプラインを本番運用に配置する方法について説明します
最後に、このコースでは、Lakeflow 宣言型パイプライン内の APPLY CHANGES INTO 構文を使用して変更データキャプチャ (CDC) を実装し、slowly changing dimensions (SCD タイプ 1 および 2) を管理し、ユーザーが CDC を独自のパイプラインに統合する準備をする方法について説明します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28477","entityUrl":{"path":"/jp/training/catalog/databricks-fundamentals-accreditation-japanese-2337"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-fundamentals-accreditation-japanese-2337"}}],"nid":28477,"vid":217782,"title":"Databricks Fundamentals Accreditation - Japanese","price":"0.00","duration":1800,"body":{"processed":"Databricks Fundamentals 認定へようこそ。この 10 問のクイズでは、Databricks Data Intelligence Platform に関する知識をテストします。このクイズに合格すると、バッジ ベンダーである Accredible からバッジが (48 時間以内に) 授与されます。幸運を！
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28065","entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-3972"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-3972"}}],"nid":28065,"vid":217370,"title":"Databricks Data Privacy - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコンテンツは、Databricks内でのデータプライバシー管理に関する包括的なガイドを提供します。Delta Lakeアーキテクチャ、リージョナルデータ分離、GDPR/CCPAコンプライアンス、チェンジデータフィード（CDF）の使用といった主要トピックを網羅しています。実践的なデモとハンズオンラボを通じて、参加者は機密データの保護とコンプライアンス確保のためのUnity Catalog機能の使用方法を学び、データ整合性を効果的に保護する能力を身につけます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-29T14:00:00"},"endDate":{"value":"2026-10-29T18:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-19T09:00:00"},"endDate":{"value":"2027-01-19T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28156","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4499"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-platform-administration-japanese-4499"}}],"nid":28156,"vid":217461,"title":"Get Started with Databricks Platform Administration - Japanese","price":"0.00","duration":7200,"body":{"processed":"本コースでは、Databricks Data Intelligence Platform におけるプラットフォーム管理の基礎を学びます。Databricks 環境における効果的なデータガバナンスに不可欠なコンポーネントである Unity Catalog の包括的な概要を提供します。5つのモジュールに分かれており、Databricks インフラストラクチャおよびその data intelligence platform の詳細な紹介から始まり、Databricks Workspace のウォークスルーも含まれます。Unity Catalog 内のデータガバナンスの原則を探索し、キーとなるコンセプト、アーキテクチャ、およびロールについて学びます。さらに、クラスターや SQL ウェアハウスを含む Unity Catalog メタストアとコンピュートリソースの管理についても取り上げます。最後に、権限、きめ細かなアクセス制御、およびデータオブジェクトのガバナンス方法を学ぶことで、データアクセス制御をマスターします。コース終了時には、Unity Catalog を管理して効果的なデータガバナンスを実装し、コンピュートリソースを最適化し、堅牢なデータセキュリティ戦略を実施するための必須スキルを習得できます。Databricks Labs サブスクリプションのご購入により、学習内容を実際の Databricks Workspace 環境で実践するための総合的なラボ演習もコースの締めくくりとして提供されます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28214","entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4836"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-data-governance-on-databricks-japanese-4836"}}],"nid":28214,"vid":217519,"title":"Get Started with Data Governance on Databricks - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、ハンズオンデモとキャップストーンラボを使用して、Unity Catalog および Databricks でのきめ細かなアクセス制御について説明します。 テーブルの種類、カタログとスキーマの構成、グループベースのアクセス管理、およびアクセス制御の移行戦略について学習します。 このコースには、行レベルのセキュリティと列マスキングによるきめ細かなアクセス制御の適用、属性ベースのアクセス制御、制御の組み合わせ、制御の移行、および包括的なガバナンス実装のためのラボに関するデモが含まれています。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28337","entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-japanese-3286"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-japanese-3286"}}],"nid":28337,"vid":217642,"title":"Build Data Pipelines with Lakeflow Declarative Pipelines - Japanese","price":"75.00","duration":14400,"body":{"processed":"このコースでは、複数のストリーミングテーブルとマテリアライズドビューを介した増分バッチまたはストリーミング取り込みと処理のために、DatabricksのLakeflow宣言型パイプラインを使用してデータパイプラインを構築するために必要な基本的な概念とスキルをユーザーに紹介します。 このコースは、Lakeflow 宣言的パイプライン を初めて使用するデータエンジニア向けに設計されており、増分データ処理、ストリーミングテーブル、マテリアライズドビュー、一時ビューなどのコアコンポーネントの概要を包括的に説明し、それらの特定の目的と違いを強調します
取り上げるトピックは次のとおりです:
- SQL を使用した Lakeflow のマルチファイル エディターを使用した ETL パイプラインの開発とデバッグ (Python コード例を提供)
- Lakeflow 宣言的パイプライン が パイプライン グラフを通じて パイプライン でデータの依存関係を追跡する方法
- パイプライン コンピュート リソース、データ アセット、トリガー モード、およびその他の詳細オプションの構成
次に、このコースでは、Lakeflow のデータ品質に対する期待値を紹介し、データの整合性を検証および適用するために、期待値をパイプラインに統合するプロセスをユーザーに案内します。 次に、学習者は、スケジュール オプション、本番運用モード、パイプラインのパフォーマンスと正常性を監視するためのパイプライン イベント ログの有効化など、パイプラインを本番運用に配置する方法について説明します
最後に、このコースでは、Lakeflow 宣言型パイプライン内の APPLY CHANGES INTO 構文を使用して変更データキャプチャ (CDC) を実装し、slowly changing dimensions (SCD タイプ 1 および 2) を管理し、ユーザーが CDC を独自のパイプラインに統合する準備をする方法について説明します。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28482","entityUrl":{"path":"/jp/training/catalog/advanced-data-engineering-with-databricks-japanese-2365"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/advanced-data-engineering-with-databricks-japanese-2365"}}],"nid":28482,"vid":217787,"title":"Advanced Data Engineering with Databricks - Japanese","price":"1500.00","duration":57600,"body":{"processed":"このコースは、Databricksを使った高度なデータエンジニアリングを学ぶための適切な入り口となります。以下では、このコースに含まれる4つの4時間の各モジュールについて説明します。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、最初のモジュールにおける講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Advanced Techniques with Apache Spark Declarative Pipelines
このコースでは、本番運用グレードのストリーミングパイプラインを構築するための Databricks の Apache Spark Declarative Pipelines (SDP) について学びます。実際の Lakehouse エンジニアリングに不可欠な高度なデザインパターン、堅牢なデータ品質の適用、およびクロスプラットフォーム統合を習得します。
コース全体を通じて、最新のデータ取り込みおよび処理技術を深く学び、レイアウト最適化のためのリキッドクラスタリングや、混在スキーマイベントに対応するマルチプレックスストリーミングパターンなどのツールを習得します。モジュールの終わりには、スキーマ進化を自信を持って処理し、チェンジデータキャプチャ (CDC) を自動化し、データ完全性を確保する方法を習得できます。
講義とハンズオンデモを通じて、以下のことを学びます。
• 複数ソースのデータを統合されたブロンズテーブルに取り込むマルチフローパイプラインを構築する。
• シルバーおよびゴールドレイヤー全体にリキッドクラスタリングとデータ品質 Expectations を適用する。
• クロスプラットフォームのデータアクセスのために Iceberg UniForm を使用したマルチプレックスパターンを実装する。
• AUTO CDC INTO を使用して SCD Type 2 の履歴トラッキングを自動化する。
• 無効なレコードを監査・管理するためのゼロデータロス隔離パイプラインを設計する。
Databricks Data Privacy
このコンテンツは、Databricks内でのデータプライバシー管理に関する包括的なガイドを提供します。Delta Lakeアーキテクチャ、リージョナルデータ分離、GDPR/CCPAコンプライアンス、チェンジデータフィード（CDF）の使用といった主要トピックを網羅しています。実践的なデモとハンズオンラボを通じて、参加者は機密データの保護とコンプライアンス確保のためのUnity Catalog機能の使用方法を学び、データ整合性を効果的に保護する能力を身につけます。
Databricks Performance Optimization
このコースでは、SparkとDelta Lakeを用いたワークロードと物理レイアウトの最適化手法、およびSpark UIの分析によるパフォーマンス評価とアプリケーションのデバッグ方法を学びます。ストリーミング、流動的クラスタリング、データスキップ、キャッシュ、Photonsなどのトピックを網羅します。
Automated Deployment with Declarative Automation Bundles
このコースでは、DevOps の原則と Databricks プロジェクトへの適用について包括的に学習します。まず、DevOps、DataOps、継続的インテグレーション（CI）、継続的デプロイメント（CD）、およびテストの中核となる概念の概要を説明し、これらの原則をデータエンジニアリングパイプラインに適用する方法を探ります。
次に、CI/CD プロセスにおける継続的デプロイメントに焦点を当て、プロジェクトのデプロイメントに使用する Databricks REST API、SDK、CLI などのツールについて説明します。Declarative Automation Bundles（DABs）の概念と、CI/CD プロセスにおける位置づけを学びます。DABs の主要なコンポーネント、フォルダー構造、および Databricks のさまざまなターゲット環境へのデプロイメントを効率化する方法について詳しく解説します。また、Databricks CLI を使用して、異なる構成を持つ複数の環境向けに Declarative Automation Bundles に変数を追加し、変更、検証、デプロイ、および実行する方法についても学習します。
最後に、Declarative Automation Bundles をローカルで構築、テスト、およびデプロイするためのインタラクティブ開発環境（IDE）として Visual Studio Code を紹介し、開発プロセスの最適化を図ります。コースの締めくくりとして、GitHub Actions を使用してデプロイメントパイプラインを自動化し、Declarative Automation Bundles を活用した CI/CD ワークフローを強化する方法を紹介します。
このコースを修了すると、DevOps プラクティスを通じて効率性を向上させながら、Declarative Automation Bundles を使用して Databricks プロジェクトのデプロイメントを自動化できるようになります。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-01T09:00:00"},"endDate":{"value":"2026-10-02T17:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28073","entityUrl":{"path":"/jp/training/catalog/aibi-for-data-analysts-japanese-4010"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/aibi-for-data-analysts-japanese-4010"}}],"nid":28073,"vid":217378,"title":"AI/BI for Data Analysts - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、データアナリストが Databricks で AI/BI Dashboards を設計、作成、公開、運用する方法を学びます。AI/BI Dashboards は、ガバナンスの効いた Unity Catalog のデータを、インタラクティブな可視化、フィルター、Genie 連携と組み合わせることで、ビジネスユーザーがコードを書かずに回答を探索できるようにします。
このコースは、1 つのエンドツーエンドの構築を通じて進めます。まず Unity Catalog のソーステーブルから始め、最終的に公開・監視された複数ページのダッシュボードを完成させます。その過程で、ダッシュボードが Databricks の AI/BI 製品ファミリー全体の中でどのように位置づけられるか、また Genie、データセット、可視化、フィルターがワークフローのどこに当てはまるかを学びます。
扱う内容は次のとおりです。
• AI/BI Dashboards の基礎と、それが Genie および Databricks プラットフォームの他の要素とどのように関係するか。
• Unity Catalog でのソースデータの探索と、SQL を使用した再利用可能なダッシュボードデータセットの設計。
• 可視化（KPI、トレンド、内訳）の作成と、見やすい複数ページのダッシュボードのレイアウト。
• Genie Code を使用して、自然言語のプロンプトから SQL、チャート、フィルターを作成すること。
• フィルターを追加して、ダッシュボードをインタラクティブにし、閲覧者の疑問に応えられるようにすること。
• 適切な人がダッシュボードを表示・編集できるよう、公開、共有、アクセス権の管理を行うこと。
• スケジュールされた更新、キャッシュ、使用状況の監視を伴って、ダッシュボードを本番環境で運用すること。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2027-01-28T09:00:00"},"endDate":{"value":"2027-01-28T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28158","entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4544"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4544"}}],"nid":28158,"vid":217463,"title":"Introduction to Apache Spark™ - Japanese","price":"0.00","duration":7200,"body":{"processed":"この初心者向けのコースでは、大規模なデータ処理のための Apache Spark の基礎について説明します。 Spark の分散アーキテクチャを探索し、DataFrame API をマスターし、Python を使用してデータの読み取り、書き込み、処理する方法を学習します。 実践的な演習を通じて、Sparkの変換とアクションを効率的に実行するために必要なスキルを身に付けます。
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28253","entityUrl":{"path":"/jp/training/catalog/machine-learning-with-databricks-japanese-2573"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-with-databricks-japanese-2573"}}],"nid":28253,"vid":217558,"title":"Machine Learning with Databricks - Japanese","price":"1500.00","duration":57600,"body":{"processed":"「Databricks を使った機械学習」へようこそ！
このコースは、Databricks での機械学習workflowsを習得するための第一歩です。専門の講師陣の指導のもと、データ準備、モデル開発、デプロイ、運用について深く学びます。Databricks に特化したデータ探索、モデルトレーニング、デプロイ戦略に必要なスキルを習得しましょう。コース修了時には、Databricks Platform上で機械学習のライフサイクル全体を円滑に進めるための知識と自信が身につき、堅牢な機械学習ソリューションを効率的に構築・デプロイできるようになります。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
機械学習のためのデータ準備
このコースでは、Databricks を使用した機械学習のためのデータ準備の基礎に焦点を当てています。参加者は、従来の機械学習アプリケーション向けにデータを探索、クリーニング、整理するための重要なスキルを習得します。主なトピックには、データの可視化、特徴量エンジニアリング、および最適な機能ストレージ戦略が含まれます。実践的な演習を通じて、参加者は Databricks 内で機械学習向けのデータセットを効率的に準備するための実践的な経験を積むことができます。このコースは、アソシエイトレベルのデータサイエンティストや機械学習の実践者、およびデータ準備のスキルを向上させたい方を対象としており、成功する機械学習モデルのデプロイに向けた確固たる基盤を提供します。
機械学習モデルの開発
この包括的なコースは、Databricks 上で従来の機械学習モデルを開発するための実践的なガイドを提供し、人気のある機械学習ライブラリを使用したハンズオンデモンストレーションと Workflows を重視しています。参加者は、回帰やクラスタリングなどの主要な機械学習技術を探索しながら、Databricks の強力な機能を活用します。本コースでは、モデルのトラッキングのための MLflow インテグレーション、機能管理のための Databricks Feature Store、およびハイパーパラメータチューニングのための Optuna について学習します。さらに、参加者は自然言語、MCP 接続、インストラクション、スキルを使用して機械学習のライフサイクル全体をガイドする Databricks の AI 搭載コーディングアシスタントである Genie Code を使用してモデル開発を加速する方法を学びます。コースの終わりには、学習者は Databricks 環境において機械学習モデルを効率的に開発、最適化、およびデプロイするための実践的なスキルを習得します。
機械学習モデルのデプロイ
このコースは、3つの主要な機械学習デプロイメント戦略を紹介し、Databricks上での各戦略の実装を解説することを目的としています。モデルデプロイメントの基礎を学んだ後、バッチ推論について詳しく取り上げ、バッチ推論シナリオでのモデル活用に関するハンズオンデモおよびラボを提供するとともに、パフォーマンス最適化に関する考慮事項についても説明します。コースの第2部ではパイプラインのデプロイメントを包括的に取り上げ、最終セクションではリアルタイムデプロイメントに焦点を当てます。参加者はハンズオンデモおよびラボに取り組み、Model Serving を使用したモデルのデプロイメントと、リアルタイム推論のための serving endpoint の活用を実践します。
機械学習運用（MLOps）
このコースでは、機械学習モデルの操作に関する包括的な探求を通じて、MLOps およびモデルライフサイクル管理に焦点を当てながら参加者をガイドします。最初のセグメントでは、MLOps の重要なコンポーネントとベストプラクティスを取り上げ、機械学習モデルを効果的に運用するための強固な基盤を参加者に提供します。コースの後半では、モデルライフサイクルの基礎を掘り下げ、効率的なモデル管理のために Unity Catalog と連携したモデルレジストリを使用してライフサイクルをシームレスに活用する方法を実演します。コースの終わりには、参加者は実践的な知見を得るとともに、MLOps の原則に関する総合的な理解を深め、機械学習モデルの操作という複雑な領域をナビゲートするために必要なスキルを身に付けることができます。
Languages Available: English | 日本語 | Português BR | 한국어
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注: このコースは、「Data Engineering with Databricks」コース シリーズの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28496","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-2438"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-data-engineering-japanese-2438"}}],"nid":28496,"vid":217801,"title":"Get Started with Databricks for Data Engineering - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform で基本的なデータエンジニアリングのワークフローを実行するために必要な基礎スキルを学びます。ワークスペースを操作し、Unity Catalog を使用しながら、データエンジニアが Databricks で日常的に活用する基本的な構成要素を習得します。
このコースは実践的な構成になっています。まずワークスペースの基本を理解し、その後、各トピックについてデモとラボのノートブックをペアで進めていきます。デモではインストラクターまたはガイド付きノートブックとともに概念を確認し、ラボでは学んだ内容を自分自身で実践します。
このコースで扱う内容は次のとおりです。
• Databricks Data Intelligence Platform の概要と、Databricks workspace、Unity Catalog、ノートブックの連携方法。
• Delta Lake テーブルの作成と管理。
• INSERT、UPDATE、DELETE によるデータの変更。
• Delta テーブルのバージョン履歴とタイムトラベルの確認。
• Lakeflow Connect のオプション（CTAS、アップロード UI、COPY INTO）を使用したデータの取り込み。
• ブロンズ、シルバー、ゴールド の各レイヤーを通じてデータを変換するメダリオンアーキテクチャのパイプラインの構築。
• Lakeflow ジョブ によるパイプラインの自動化。
•（ボーナス）Spark Declarative Pipelines を使用した宣言型パイプラインの構築。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28079","entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-4029"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-4029"}}],"nid":28079,"vid":217384,"title":"Databricks Data Privacy - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコンテンツは、Databricks内でのデータプライバシー管理に関する包括的なガイドを提供します。Delta Lakeアーキテクチャ、リージョナルデータ分離、GDPR/CCPAコンプライアンス、チェンジデータフィード（CDF）の使用といった主要トピックを網羅しています。実践的なデモとハンズオンラボを通じて、参加者は機密データの保護とコンプライアンス確保のためのUnity Catalog機能の使用方法を学び、データ整合性を効果的に保護する能力を身につけます。
注記：このコースは「Databricksによる高度なデータエンジニアリング」シリーズの2回目です。
Languages Available: English | 日本語 | Português BR
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28159","entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4545"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/introduction-to-apache-spark-japanese-4545"}}],"nid":28159,"vid":217464,"title":"Introduction to Apache Spark™ - Japanese","price":"75.00","duration":10800,"body":{"processed":"この初心者向けのコースでは、大規模なデータ処理のための Apache Spark の基礎について説明します。 Spark の分散アーキテクチャを探索し、DataFrame API をマスターし、Python を使用してデータの読み取り、書き込み、処理する方法を学習します。 実践的な演習を通じて、Sparkの変換とアクションを効率的に実行するために必要なスキルを身に付けます。
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28254","entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-2578"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-model-development-japanese-2578"}}],"nid":28254,"vid":217559,"title":"Machine Learning Model Development - Japanese","price":"750.00","duration":14400,"body":{"processed":"この包括的なコースは、Databricks 上で従来の機械学習モデルを開発するための実践的なガイドを提供し、人気のある機械学習ライブラリを使用したハンズオンデモンストレーションと Workflows を重視しています。参加者は、回帰やクラスタリングなどの主要な機械学習技術を探索しながら、Databricks の強力な機能を活用します。本コースでは、モデルのトラッキングのための MLflow インテグレーション、機能管理のための Databricks Feature Store、およびハイパーパラメータチューニングのための Optuna について学習します。さらに、参加者は自然言語、MCP 接続、インストラクション、スキルを使用して機械学習のライフサイクル全体をガイドする Databricks の AI 搭載コーディングアシスタントである Genie Code を使用してモデル開発を加速する方法を学びます。コースの終わりには、学習者は Databricks 環境において機械学習モデルを効率的に開発、最適化、およびデプロイするための実践的なスキルを習得します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-21T09:00:00"},"endDate":{"value":"2026-10-21T13:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-03T09:00:00"},"endDate":{"value":"2026-12-03T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28343","entityUrl":{"path":"/jp/training/catalog/data-ingestion-with-delta-lake-japanese-3300"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-ingestion-with-delta-lake-japanese-3300"}}],"nid":28343,"vid":218589,"title":"Data Ingestion with Delta Lake - Japanese","price":"0.00","duration":14400,"body":{"processed":"このコースでは、データプロフェッショナルがDatabricksインテリジェンスプラットフォームを活用してETLパイプラインを本番運用化するための準備をします。 受講者は、Spark SQLとPythonでDelta Live Tablesを使用して、さまざまなデータソースからレイクハウスへの新しいデータを段階的に処理するパイプラインを定義およびスケジュールします。 また、Databricks Workflows でタスクをオーケストレーションし、Databricks Repos でコードのステータスを昇格 (Promote) します。
注: このコースは、「Data Engineering with Databricks」コース シリーズの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28498","entityUrl":{"path":"/jp/training/catalog/data-analysis-with-databricks-japanese-2442"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-analysis-with-databricks-japanese-2442"}}],"nid":28498,"vid":217803,"title":"Data Analysis with Databricks - Japanese","price":"1000.00","duration":28800,"body":{"processed":"このコースでは、Databricks SQLの包括的な入門を提供します。学習者はデータのインジェスト、クエリの作成、ビジュアライゼーションとダッシュボードの作成、アラートの設定を行います。このコースは、Databricks認定データアナリストアソシエイト試験を受験するための準備コースです。
このコースは4時間のモジュール2つで構成されている。
SQL Analytics on Databricks
このコースでは、特に Databricks SQL に焦点を当てて、データ分析に Databricks を効果的に使用する方法を学習します。 Databricks データアナリストの責任には、関連データの検索、潜在的なアプリケーションのための分析、貴重なビジネスインサイトを提供する形式への変換が含まれます。
また、データオブジェクトの管理における自分の役割と、ノートブック、SQL エディター、Databricks SQL などのツールを使用して Databricks データインテリジェンスプラットフォーム内でデータオブジェクトを操作する方法についても理解できます。
さらに、データ資産とプラットフォーム全体の管理における Unity Catalog の重要性についても学習します。 最後に、このコースでは、Databricksがパフォーマンスの最適化を促進する方法の概要を説明し、クエリーインサイトにアクセスして、DatabricksでSQLアナリティクスを実行するときにバックグラウンドで発生するプロセスを理解する方法について説明します。
AI/BI for Data Analysts
このコースでは、データアナリストが Databricks で AI/BI Dashboards を設計、作成、公開、運用する方法を学びます。AI/BI Dashboards は、ガバナンスの効いた Unity Catalog のデータを、インタラクティブな可視化、フィルター、Genie 連携と組み合わせることで、ビジネスユーザーがコードを書かずに回答を探索できるようにします。
このコースは、1 つのエンドツーエンドの構築を通じて進めます。まず Unity Catalog のソーステーブルから始め、最終的に公開・監視された複数ページのダッシュボードを完成させます。その過程で、ダッシュボードが Databricks の AI/BI 製品ファミリー全体の中でどのように位置づけられるか、また Genie、データセット、可視化、フィルターがワークフローのどこに当てはまるかを学びます。
扱う内容は次のとおりです。
• AI/BI Dashboards の基礎と、それが Genie および Databricks プラットフォームの他の要素とどのように関係するか。
• Unity Catalog でのソースデータの探索と、SQL を使用した再利用可能なダッシュボードデータセットの設計。
• 可視化（KPI、トレンド、内訳）の作成と、見やすい複数ページのダッシュボードのレイアウト。
• Genie Code を使用して、自然言語のプロンプトから SQL、チャート、フィルターを作成すること。
• フィルターを追加して、ダッシュボードをインタラクティブにし、閲覧者の疑問に応えられるようにすること。
• 適切な人がダッシュボードを表示・編集できるよう、公開、共有、アクセス権の管理を行うこと。
• スケジュールされた更新、キャッシュ、使用状況の監視を伴って、ダッシュボードを本番環境で運用すること。
注記：Databricks Academyでは、Databricks環境内での教室セッションをノートブック形式に移行し、講義用スライドデッキの使用を終了します。講義ノートブックはVocareumラボ環境でアクセス可能です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-26T09:00:00"},"endDate":{"value":"2026-10-26T17:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-11-24T09:00:00"},"endDate":{"value":"2026-11-24T17:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28080","entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-4030"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-data-privacy-japanese-4030"}}],"nid":28080,"vid":217385,"title":"Databricks Data Privacy - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコンテンツは、Databricks内でのデータプライバシー管理に関する包括的なガイドを提供します。Delta Lakeアーキテクチャ、リージョナルデータ分離、GDPR/CCPAコンプライアンス、チェンジデータフィード（CDF）の使用といった主要トピックを網羅しています。実践的なデモとハンズオンラボを通じて、参加者は機密データの保護とコンプライアンス確保のためのUnity Catalog機能の使用方法を学び、データ整合性を効果的に保護する能力を身につけます。
注記：このコースは「Databricksによる高度なデータエンジニアリング」シリーズの2回目です。
Languages Available: English | 日本語 | Português BR
このハンズオンコースでは、Apache Spark を使用したスケーラブルなデータ処理を習得します。 Spark の DataFrame API を使用して、効率的な ETL パイプラインを構築し、高度な分析を実行し、分散データ変換を最適化する方法を学びます。 グループ化、集計、結合、集合演算、ウィンドウ関数について調べます。 配列、マップ、構造体などの複雑なデータ型を操作しながら、パフォーマンス最適化のベストプラクティスを適用します。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28255","entityUrl":{"path":"/jp/training/catalog/machine-learning-model-deployment-japanese-2580"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-model-deployment-japanese-2580"}}],"nid":28255,"vid":217560,"title":"Machine Learning Model Deployment - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースは、3つの主要な機械学習デプロイメント戦略を紹介し、Databricks上での各戦略の実装を解説することを目的としています。モデルデプロイメントの基礎を学んだ後、バッチ推論について詳しく取り上げ、バッチ推論シナリオでのモデル活用に関するハンズオンデモおよびラボを提供するとともに、パフォーマンス最適化に関する考慮事項についても説明します。コースの第2部ではパイプラインのデプロイメントを包括的に取り上げ、最終セクションではリアルタイムデプロイメントに焦点を当てます。参加者はハンズオンデモおよびラボに取り組み、Model Serving を使用したモデルのデプロイメントと、リアルタイム推論のための serving endpoint の活用を実践します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
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注記：このコースは「Advanced Data Engineering with Databricks」コースの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28088","entityUrl":{"path":"/jp/training/catalog/apache-spark-programming-with-databricks-japanese-4072"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/apache-spark-programming-with-databricks-japanese-4072"}}],"nid":28088,"vid":217393,"title":"Apache Spark Programming with Databricks - Japanese","price":"1500.00","duration":57600,"body":{"processed":"このコースは、Databricksを使ったApache Sparkプログラミングを学ぶための適切な入口となります。
以下では、このコースに含まれる4つのモジュール（4時間）について説明します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Introduction to Apache Spark
この初心者向けコースでは、大規模データ処理のための Apache Spark の基礎を学びます。Spark の分散アーキテクチャを探索し、DataFrame API を習得し、Python を使用してデータの読み込み、書き込み、処理を行う方法を学びます。ハンズオン演習を通じて、Spark の変換処理とアクションを効率的に実行するために必要なスキルを身につけます。
Developing Applications with Apache Spark
Apache Sparkを使ったスケーラブルなデータ処理をマスターするコースです。効率的なETLパイプラインの構築、高度なアナリティクスの実行、およびSparkのDataFrame APIを使用した分散データの変換処理の最適化について学びます。グループ化、集計、結合、集合操作、およびウィンドウ関数を探索します。配列、マップ、構造体などの複合データ型を扱いながら、パフォーマンス最適化のベストプラクティスを適用します。
Stream Processing and Analysis with Apache Spark
このコースでは、Databricks 上で Spark 構造化ストリーミング API を使用して、スケーラブルでフォールトトレラントなストリーム処理アプリケーションを開発する方法を学習者に解説します。
Monitoring and Optimizing Apache Spark Workloads on Databricks
このコースでは、Databricks プラットフォームのコアコンポーネントおよび Apache Spark と Delta Lake について、Lakehouse アーキテクチャ、Unity Catalog、ACIDトランザクションやテーブルメンテナンスなどのデータマネジメント技術に焦点を当てて学習します。さらに、パーティショニング、シャッフル、チューニングツールを活用してクエリーのパフォーマンスを最適化する方法や、Spark UI を使用してアプリケーションを監視しボトルネックを解消する方法についても学びます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28162","entityUrl":{"path":"/jp/training/catalog/developing-applications-with-apache-spark-japanese-4554"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/developing-applications-with-apache-spark-japanese-4554"}}],"nid":28162,"vid":217467,"title":"Developing Applications with Apache Spark™ - Japanese","price":"0.00","duration":7200,"body":{"processed":"このハンズオンコースでは、Apache Spark を使用したスケーラブルなデータ処理を習得します。 Spark の DataFrame API を使用して、効率的な ETL パイプラインを構築し、高度な分析を実行し、分散データ変換を最適化する方法を学びます。 グループ化、集計、結合、集合演算、ウィンドウ関数について調べます。 配列、マップ、構造体などの複雑なデータ型を操作しながら、パフォーマンス最適化のベストプラクティスを適用します。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28256","entityUrl":{"path":"/jp/training/catalog/machine-learning-operations-japanese-2582"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/machine-learning-operations-japanese-2582"}}],"nid":28256,"vid":217561,"title":"Machine Learning Operations - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、機械学習モデルの操作に関する包括的な探求を通じて、MLOps およびモデルライフサイクル管理に焦点を当てながら参加者をガイドします。最初のセグメントでは、MLOps の重要なコンポーネントとベストプラクティスを取り上げ、機械学習モデルを効果的に運用するための強固な基盤を参加者に提供します。コースの後半では、モデルライフサイクルの基礎を掘り下げ、効率的なモデル管理のために Unity Catalog と連携したモデルレジストリを使用してライフサイクルをシームレスに活用する方法を実演します。コースの終わりには、参加者は実践的な知見を得るとともに、MLOps の原則に関する総合的な理解を深め、機械学習モデルの操作という複雑な領域をナビゲートするために必要なスキルを身に付けることができます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-30T09:00:00"},"endDate":{"value":"2026-10-30T13:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-17T09:00:00"},"endDate":{"value":"2026-12-17T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28354","entityUrl":{"path":"/jp/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-japanese-3375"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-japanese-3375"}}],"nid":28354,"vid":217659,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Japanese","price":"75.00","duration":14400,"body":{"processed":"このコースでは、計算モデル、ストリーミング読み取りの構成、ストリーミング環境でのデータ品質の維持など、Spark 構造化ストリーミングとDelta Lakeの包括的な理解を提供します。
注記：このコースは「Advanced Data Engineering with Databricks」コースの一部です。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28089","entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4074"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4074"}}],"nid":28089,"vid":217394,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks プラットフォームのコアコンポーネントおよび Apache Spark と Delta Lake について、Lakehouse アーキテクチャ、Unity Catalog、ACIDトランザクションやテーブルメンテナンスなどのデータマネジメント技術に焦点を当てて学習します。さらに、パーティショニング、シャッフル、チューニングツールを活用してクエリーのパフォーマンスを最適化する方法や、Spark UI を使用してアプリケーションを監視しボトルネックを解消する方法についても学びます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28170","entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4568"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4568"}}],"nid":28170,"vid":217475,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、セキュアなデータガバナンス、アクセスコントロール、リネージトラッキングのためのUnity Catalogを中心に、スケーラブルなデータワークフローのためのレイクハウスアーキテクチャとメダリオン設計を探求します。カリキュラムには、Delta Lakeを使用した信頼性の高いACID準拠のパイプラインの構築も含まれます。パーティショニング、キャッシング、クエリチューニングなどのSpark最適化テクニックを検証し、パフォーマンスモニタリング、トラブルシューティング、効率的なデータエンジニアリングとアナリティクスのベストプラクティスを学び、現実世界の課題に取り組みます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28257","entityUrl":{"path":"/jp/training/catalog/data-preparation-for-machine-learning-japanese-2585"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/data-preparation-for-machine-learning-japanese-2585"}}],"nid":28257,"vid":217562,"title":"Data Preparation for Machine Learning - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、Databricks を使用した機械学習のためのデータ準備の基礎に焦点を当てています。参加者は、従来の機械学習アプリケーション向けにデータを探索、クリーニング、整理するための重要なスキルを習得します。主なトピックには、データの可視化、特徴量エンジニアリング、および最適な機能ストレージ戦略が含まれます。実践的な演習を通じて、参加者は Databricks 内で機械学習向けのデータセットを効率的に準備するための実践的な経験を積むことができます。このコースは、アソシエイトレベルのデータサイエンティストや機械学習の実践者、およびデータ準備のスキルを向上させたい方を対象としており、成功する機械学習モデルのデプロイに向けた確固たる基盤を提供します。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-02T09:00:00"},"endDate":{"value":"2026-12-02T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28358","entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3395"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-japanese-3395"}}],"nid":28358,"vid":217663,"title":"Get Started with SQL Analytics and BI on Databricks - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform と、データアナリストが日常的な SQL アナリティクスおよび BI 業務に必要なコアスキルを紹介します。ワークスペースと Unity Catalog のナビゲーション、Serverless SQL Warehouse からの Unity Catalog マネージドテーブルに対する SQL クエリの記述、Genie Code を使用した SQL の生成とデバッグ、Delta Lake の操作（DML、バージョン履歴、タイムトラベル、およびリストア）、AI/BI ダッシュボードの構築と公開、そして会話型アナリティクスのための Genie Agents の作成について学習します。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-13T10:00:00"},"endDate":{"value":"2026-10-13T12:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-11-13T10:00:00"},"endDate":{"value":"2026-11-13T12:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2026-12-10T10:00:00"},"endDate":{"value":"2026-12-10T12:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-15T10:00:00"},"endDate":{"value":"2027-01-15T12:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28090","entityUrl":{"path":"/jp/training/catalog/developing-applications-with-apache-spark-japanese-4077"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/developing-applications-with-apache-spark-japanese-4077"}}],"nid":28090,"vid":217395,"title":"Developing Applications with Apache Spark - Japanese","price":"750.00","duration":14400,"body":{"processed":"Apache Sparkを使ったスケーラブルなデータ処理をマスターするコースです。効率的なETLパイプラインの構築、高度なアナリティクスの実行、およびSparkのDataFrame APIを使用した分散データの変換処理の最適化について学びます。グループ化、集計、結合、集合操作、およびウィンドウ関数を探索します。配列、マップ、構造体などの複合データ型を扱いながら、パフォーマンス最適化のベストプラクティスを適用します。
注：SCORM形式の講義ファイルをご利用の際は、コンテンツをすべて終了した後、必ずSCORMウィンドウを閉じてください。「next lesson」ボタンをクリックしないでください。クリックすると、SCORMモジュールが完了として認識されなくなる可能性があります。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-22T09:00:00"},"endDate":{"value":"2026-12-22T13:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28171","entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4569"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-japanese-4569"}}],"nid":28171,"vid":217476,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Japanese","price":"75.00","duration":10800,"body":{"processed":"このコースでは、セキュアなデータガバナンス、アクセスコントロール、リネージトラッキングのためのUnity Catalogを中心に、スケーラブルなデータワークフローのためのレイクハウスアーキテクチャとメダリオン設計を探求します。カリキュラムには、Delta Lakeを使用した信頼性の高いACID準拠のパイプラインの構築も含まれます。パーティショニング、キャッシング、クエリチューニングなどのSpark最適化テクニックを検証し、パフォーマンスモニタリング、トラブルシューティング、効率的なデータエンジニアリングとアナリティクスのベストプラクティスを学び、現実世界の課題に取り組みます。
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28286","entityUrl":{"path":"/jp/training/catalog/agent-evaluation-on-databricks-japanese-2854"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/agent-evaluation-on-databricks-japanese-2854"}}],"nid":28286,"vid":217591,"title":"Agent Evaluation on Databricks - Japanese","price":"750.00","duration":14400,"body":{"processed":"このコースでは、MLflow の評価frameworkを使用して AI エージェントを体系的に評価する方法を学び、従来のソフトウェア テストでは対処できない非決定論的 AI システム固有の課題に対処します。 学生は、正確性や安全性などの一般的な基準のための組み込みのジャッジ、ビジネス固有の要件のためのガイドラインのジャッジ、特殊なニーズのためのカスタムジャッジなど、さまざまな評価アプローチを実装する方法を学びます。 このコースでは、キュレーションされたデータセットを使用したオフライン評価とオンラインの本番モニタリングの両方をカバーし、MLflow のトレース機能を使用してエージェントの実行パターンを理解し、さまざまなタイプの関係者から人間によるフィードバックを収集する実践的な経験を積むことができます。 実践的なデモンストレーションとラボを通じて、受講者はAIエージェント開発ライフサイクル全体を通じて継続的な品質改善を推進する評価workflowsを作成するスキルを身に付けます。
注意：Databricks Academyでは、Databricks環境内でのクラスルームセッションをノートブックベースのフォーマットに移行しており、スライドデッキを用いた講義は廃止されます。講義用ノートブックには、Vocareumラボ環境からアクセスできます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-09-30T09:00:00"},"endDate":{"value":"2026-09-30T13:00:00"},"timezone":"Asia/Tokyo"}},{"entity":{"startDate":{"value":"2027-01-26T14:00:00"},"endDate":{"value":"2027-01-26T18:00:00"},"timezone":"Asia/Tokyo"}}]},{"id":"28387","entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3519"},"entityTranslations":[{"entityLanguage":{"id":"ja"},"entityUrl":{"path":"/jp/training/catalog/get-started-with-databricks-for-machine-learning-japanese-3519"}}],"nid":28387,"vid":217692,"title":"Get Started with Databricks for Machine Learning - Japanese","price":"0.00","duration":7200,"body":{"processed":"このコースでは、Databricks Data Intelligence Platform を使用してシンプルなデータサイエンスおよび機械学習ワークフローを実行するための基本的なスキルを習得します。ワークスペースのツアーを通じて、ノートブックの操作方法を学びます。探索的データ解析と特徴量エンジニアリングを探索し、MLflow を使用してモデルを追跡・管理し、Databricks Genie Code を使用してエクスペリメントを行い、Databricks Model Serving を使用してモデルをデプロイします。最後に、エンドツーエンドの機械学習をカバーする包括的なラボでこれらのスキルを統合します。
Databricks Free Edition account のアカウントを作成すれば、実践的な環境でデモを実際に試すことができます。
注: Databricks Academyは、Databricks環境内の教室セッションをノートブックベースの形式へ移行しており、講義でのスライドデッキの使用を終了します。講義用ノートブックはVocareumのラボ環境で利用できます。
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]}]},"coursesKO":{"entities":[{"id":"33959","entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-databricks-asset-bundles-korean-3939"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-databricks-asset-bundles-korean-3939"}}],"nid":33959,"vid":254350,"title":"Automated Deployment with Databricks Asset Bundles - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정은 DevOps 원칙과 이를 Databricks 프로젝트에 적용하는 방법을 포괄적으로 검토합니다. 핵심 DevOps, DataOps, 지continuous integration (CI), continuous deployment (CD), 테스트에 대한 개요로 시작하여 이러한 원칙을 데이터 엔지니어링 파이프라인에 적용하는 방법을 탐구합니다.
이어서 CI/CD 프로세스 내 지속적 배포에 초점을 맞추며, 프로젝트 배포를 위한 Databricks REST API, SDK, CLI와 같은 도구를 살펴봅니다. Databricks Asset Bundles(DAB)와 CI/CD 프로세스 내에서의 역할을 학습하게 됩니다. 주요 구성 요소, 폴더 구조, Databricks 내 다양한 대상 환경에 걸친 배포 간소화 방식을 심층적으로 다룹니다. 또한 Databricks CLI를 활용하여 서로 다른 구성의 다중 환경에 대해 변수 추가, 수정, 검증, 배포 및 실행하는 방법을 익히게 됩니다.
마지막으로, Visual Studio Code를 인터랙티브 개발 환경(IDE)으로 활용하여 로컬에서 Databricks Asset Bundles를 빌드, 테스트, 배포하는 방법을 소개함으로써 개발 프로세스를 최적화합니다. GitHub Actions를 활용한 배포 파이프라인 자동화를 통해 Databricks Asset Bundles의 CI/CD 워크플로우를 강화하는 방법에 대한 소개로 강좌를 마무리합니다.
본 과정 수료 시, Databricks Asset Bundles를 활용한 Databricks 프로젝트 배포 자동화 역량을 갖추게 되어 DevOps 관행을 통해 효율성을 향상시킬 수 있습니다.
참고: 이 강좌는 ‘Databricks을 사용한 고급 데이터 엔지니어링’ 시리즈의 네 번째 강좌입니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"33955","entityUrl":{"path":"/kr/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-korean-6634"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-korean-6634"}}],"nid":33955,"vid":254345,"title":"Building Databricks Apps with Genie Code and Lakebase - Korean","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps를 사용하면 Databricks 플랫폼에서 직접 대화형 데이터 및 AI 애플리케이션을 빌드하고 배포할 수 있습니다. 하지만 성공적인 AI 지원 개발은 단순히 코드를 생성하는 것 이상으로, 효과적인 워크플로를 개발하는 것이 핵심입니다.
이 실습 과정에서는 Genie Code를 AI 개발 어시스턴트로 활용하여 Lakebase 기반의 Databricks App을 처음부터 빌드합니다. 과정을 진행하면서 AI 지원 개발에 대한 실용적이고 반복 가능한 접근 방식을 배웁니다. 여기에는 코드 생성 전 의도를 명확히 명세하기, 작고 검증 가능한 단위로 작업하기, 재사용 가능한 Genie Code Skills 활용하기, 그리고 AI가 생성한 결과물을 단순히 수용하지 않고 검토하고 개선해야 할 대상으로 다루기가 포함됩니다.
Databricks App을 생성 및 배포하고, Lakebase 데이터베이스를 트랜잭션 저장소로 프로비저닝하여 연결하고, CRUD 운영을 구현하며, Genie Code를 사용하여 일반적인 개발 작업을 가속화합니다. 과정을 마치면 작동하는 애플리케이션을 갖추게 될 뿐만 아니라, 향후 소프트웨어 프로젝트에서 AI와 효과적으로 협업하기 위한 실용적인 프레임워크도 습득하게 됩니다.
참고: Databricks Academy는 Databricks 환경 내 강의실 세션을 노트북 기반 형식으로 전환하고 있으며, 강의에서 슬라이드 자료 사용을 중단합니다. 강의 노트북은 Vocareum 실습 환경에서 이용할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33898","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3779"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3779"}}],"nid":33898,"vid":254033,"title":"Get Started with Databricks for Generative AI - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 실용적인 입문 과정으로, 생성형 AI 시스템을 구축하고 배포하기 위한 핵심 구성 요소와 기능에 중점을 둡니다. 참가자들은 Databricks가 확장 가능한 생성형 AI 솔루션 개발을 어떻게 지원하는지 학습하고, AI Search, Agent Framework, 그리고 모델 추적 및 로깅을 위한 MLflow의 생성형 AI 기능과 같은 도구들을 탐험합니다. 이 과정에는 Retrieval-Augmented Generation (RAG) 파이프라인의 구축 및 평가, 생성형 AI 에이전트 배포, 그리고 성능 최적화를 위한 평가 프레임워크 활용에 관한 실습 경험이 포함됩니다. 과정을 마치면 학습자들은 Databricks Data Intelligence Platform에서 일반적인 생성형 AI 애플리케이션을 설계, 배포 및 모니터링할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33899","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3781"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3781"}}],"nid":33899,"vid":254034,"title":"Get Started with Databricks for Generative AI - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 실용적인 입문 과정으로, 생성형 AI 시스템을 구축하고 배포하기 위한 핵심 구성 요소와 기능에 중점을 둡니다. 참가자들은 Databricks가 확장 가능한 생성형 AI 솔루션 개발을 어떻게 지원하는지 학습하고, AI Search, Agent Framework, 그리고 모델 추적 및 로깅을 위한 MLflow의 생성형 AI 기능과 같은 도구들을 탐험합니다. 이 과정에는 Retrieval-Augmented Generation (RAG) 파이프라인의 구축 및 평가, 생성형 AI 에이전트 배포, 그리고 성능 최적화를 위한 평가 프레임워크 활용에 관한 실습 경험이 포함됩니다. 과정을 마치면 학습자들은 Databricks Data Intelligence Platform에서 일반적인 생성형 AI 애플리케이션을 설계, 배포 및 모니터링할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33810","entityUrl":{"path":"/kr/training/catalog/get-started-with-ai-agents-on-databricks-korean-4764"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-ai-agents-on-databricks-korean-4764"}}],"nid":33810,"vid":253347,"title":"Get Started with AI Agents on Databricks - Korean","price":"0.00","duration":0,"body":{"processed":"이 과정은 AI 에이전트, 현대 AI 애플리케이션에서의 역할, 그리고 Databricks 플랫폼에서 AI 에이전트 애플리케이션을 구축하는 방법에 대한 입문 과정입니다. AI 에이전트의 원칙, 기존 AI 시스템과의 차이점을 학습하고, 주요 구성 요소를 탐험합니다. 인터랙티브 데모와 실습을 통해 Databricks AI 및 Agent Bricks를 활용하여 Databricks에서 AI 에이전트를 구축, 배포 및 평가하는 방법을 익힙니다. 이 과정을 마치면 Databricks Data + AI Platform을 사용하여 AI 에이전트를 생성하고 배포하는 방법을 이해하게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-19T14:00:00"},"endDate":{"value":"2026-11-19T16:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-12-03T14:00:00"},"endDate":{"value":"2026-12-03T16:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2027-01-19T14:00:00"},"endDate":{"value":"2027-01-19T16:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"33344","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6525"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6525"}}],"nid":33344,"vid":252751,"title":"Get Started with Databricks: End to End - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 포괄적인 실습 입문 과정입니다. 워크스페이스에서 시작하여 AI 및 머신 러닝 소개로 마무리되는 하나의 엔드투엔드 여정을 따라가며, Databricks에서 데이터를 다루는 데 필요한 일상적인 기술을 습득합니다.
이 과정에서 다루는 내용:
이 과정을 마치면 Databricks 탐색, Unity Catalog에서 데이터 검색 및 거버넌스, AI 지원을 통한 SQL 및 노트북 코드 작성, 대시보드 구축, Genie를 활용한 데이터 탐색에 익숙해질 것입니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 반드시 SCORM 창을 닫아 주세요. ‘Next Lesson’ 버튼을 클릭하지 마세요. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33345","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6526"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6526"}}],"nid":33345,"vid":252752,"title":"Get Started with Databricks: End to End - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 포괄적인 실습 입문 과정입니다. 워크스페이스에서 시작하여 AI 및 머신 러닝 소개로 마무리되는 하나의 엔드투엔드 여정을 따라가며, Databricks에서 데이터를 다루는 데 필요한 일상적인 기술을 습득합니다.
이 과정에서 다루는 내용:
이 과정을 마치면 Databricks 탐색, Unity Catalog에서 데이터 검색 및 거버넌스, AI 지원을 통한 SQL 및 노트북 코드 작성, 대시보드 구축, Genie를 활용한 데이터 탐색에 익숙해질 것입니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 반드시 SCORM 창을 닫아 주세요. ‘Next Lesson’ 버튼을 클릭하지 마세요. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32117","entityUrl":{"path":"/kr/training/catalog/ai-agent-fundamentals-accreditation-korean-4738"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/ai-agent-fundamentals-accreditation-korean-4738"}}],"nid":32117,"vid":251044,"title":"AI Agent Fundamentals Accreditation - Korean","price":"0.00","duration":1800,"body":{"processed":"AI 에이전트 기초 인증 퀴즈에 오신 것을 환영합니다. 이 20문항 퀴즈에서는 AI 에이전트의 기초 지식, 기업 적용 사례, 그리고 Databricks의 Mosaic AI 및 Agent Bricks를 활용한 구축 및 배포 방법에 대한 이해도를 평가합니다. 퀴즈를 성공적으로 완료하시면 인증 업체인 Accredible을 통해 48시간 이내에 배지를 수여받게 됩니다. 행운을 빕니다!
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32091","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6488"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6488"}}],"nid":32091,"vid":250764,"title":"Get Started with Databricks Apps - Korean","price":"0.00","duration":3600,"body":{"processed":"이 과정에서는 개발자가 Databricks 플랫폼에서 직접 안전한 데이터 및 AI 애플리케이션을 빌드하고 배포할 수 있도록 지원하는 기능인 Databricks Apps를 소개합니다. 이 과정은 주로 조직 내 비기술 사용자가 데이터 인사이트에 접근할 수 있도록 맞춤형 애플리케이션을 만들어야 하는 데이터 과학자, 데이터 엔지니어 및 개발자를 대상으로 합니다.
이 과정은 Databricks Apps의 주요 구성 요소에 대한 개요를 제공하는 것으로 시작하며, 이후 외부 서비스 및 Databricks 리소스와 통합되는 간단한 앱을 배포하는 내용으로 이어집니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32092","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6494"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6494"}}],"nid":32092,"vid":250765,"title":"Get Started with Databricks Apps - Korean","price":"75.00","duration":7200,"body":{"processed":"이 과정에서는 개발자가 Databricks 플랫폼에서 직접 안전한 데이터 및 AI 애플리케이션을 빌드하고 배포할 수 있도록 지원하는 기능인 Databricks Apps를 소개합니다. 이 과정은 주로 조직 내 비기술 사용자가 데이터 인사이트에 접근할 수 있도록 맞춤형 애플리케이션을 만들어야 하는 데이터 과학자, 데이터 엔지니어 및 개발자를 대상으로 합니다.
이 과정은 Databricks Apps의 주요 구성 요소에 대한 개요를 제공하는 것으로 시작하며, 이후 외부 서비스 및 Databricks 리소스와 통합되는 간단한 앱을 배포하는 내용으로 이어집니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32076","entityUrl":{"path":"/kr/training/catalog/databricks-fundamentals-korean-2752"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-fundamentals-korean-2752"}}],"nid":32076,"vid":250692,"title":"Databricks Fundamentals - Korean","price":"0.00","duration":3600,"body":{"processed":"이 과정은 Databricks 및 Databricks Platform에 대한 기초 입문 과정입니다. 현대 데이터 및 AI 팀이 직면한 문제, 플랫폼의 핵심인 레이크하우스 개념, 플랫폼이 제공하는 제품 및 기능, 통합 거버넌스를 통해 데이터와 AI의 신뢰성을 유지하는 방법, 그리고 워크스페이스 자체에 대한 안내를 소개합니다.
영상은 권장 순서로 제공되지만, 원하시는 순서대로 시청하셔도 됩니다. 또한 Databricks Fundamentals 인증 평가에 응시하기 전에 제공된 모든 영상 콘텐츠를 시청하실 것을 권장합니다.
Databricks 또는 데이터 플랫폼에 대한 사전 기술 지식은 필요하지 않습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32046","entityUrl":{"path":"/kr/training/catalog/generative-ai-fundamentals-korean-2780"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/generative-ai-fundamentals-korean-2780"}}],"nid":32046,"vid":250264,"title":"Generative AI Fundamentals - Korean","price":"0.00","duration":7200,"body":{"processed":"생성형 AI는 새롭게 떠오르는 실험에서 핵심 엔터프라이즈 역량으로 발전하여, 지능형 고객 지원부터 복잡한 Workflows를 자동화하는 AI Agents에 이르기까지 모든 것을 지원하고 있습니다.
자체 데이터를 기반으로 신뢰성 있는 거버넌스를 갖추어 생성형 AI를 효과적으로 배포하는 방법을 이해하는 조직이 각 산업에서 앞서 나갈 것입니다. 그러나 매주 새로운 모델이 출시되고 기능이 빠르게 진화하는 상황에서, 최신 릴리스를 쫓기보다 생성형AI를 전략적으로 평가하고 신청하는 방법을 아는 것이 더욱 중요합니다. 이 무료 온디맨드 학습을 통해 생성형 AI의 기본 개념—무엇을 할 수 있는지, 어디서 실질적인 비즈니스 가치를 제공하는지, Databricks에서 안전하게 구현하는 방법—을 빠르게 습득하십시오.
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31931","entityUrl":{"path":"/kr/training/catalog/ai-agent-fundamentals-korean-4737"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/ai-agent-fundamentals-korean-4737"}}],"nid":31931,"vid":250051,"title":"AI Agent Fundamentals - Korean","price":"0.00","duration":5400,"body":{"processed":"이 기초 과정에서는 AI agents와 Databricks의 엔터프라이즈 애플리케이션에서의 활용을 소개하며, Mosaic AI 플랫폼과 Agent Bricks를 포함합니다. 학습자는 AI agents가 무엇인지, 어떻게 작동하는지, 그리고 복잡한 작업을 처리하기 위해 인간의 추론을 어떻게 모방하는지 살펴보게 됩니다.
이 과정은 실제 agent 활용 사례를 다루며, 에이전틱 워크플로우 및 멀티 에이전트 시스템과 같은 고급 주제에 대한 기본적인 소개를 제공합니다. 또한 Agent Bricks가 다양한 애플리케이션에서 엔터프라이즈 수준의 agents 개발을 어떻게 간소화하는지 살펴보고, Databricks에서 agents를 구축하고 활용하는 방법을 보여주는 데모도 포함되어 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31907","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-6443"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-6443"}}],"nid":31907,"vid":249970,"title":"Get Started with Databricks for Data Warehousing - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks의 현대적인 데이터 웨어하우징 접근 방식에 대한 포괄적이고 실습 중심의 개요를 제공하며, 데이터 레이크하우스 아키텍처가 기존 데이터 웨어하우스의 강점과 클라우드의 유연성 및 확장성을 어떻게 결합하는지를 중점적으로 다룹니다. 가상의 소매업체(Vintage Audio Co.)를 대상으로 엔드투엔드 작업을 수행하면서, 워크스페이스를 탐험하고, 거버넌스가 적용된 Unity Catalog 테이블을 쿼리하며, 분석 읽기를 위해 Unity Catalog 관리형 테이블을 빠르게 유지하고, Auto Loader로 데이터를 증분 로드하고, 스타 스키마를 모델링하며, Unity Catalog 메트릭 뷰를 통해 일관된 인사이트를 제공합니다. 이 모든 작업은 AI 기반 기능(Predictive Optimization, Genie Code)이 전반에 걸쳐 내장된 단일 거버넌스 환경에서 이루어집니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31908","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-6444"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-6444"}}],"nid":31908,"vid":249971,"title":"Get Started with Databricks for Data Warehousing - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정은 Databricks의 현대적인 데이터 웨어하우징 접근 방식에 대한 포괄적이고 실습 중심의 개요를 제공하며, 데이터 레이크하우스 아키텍처가 기존 데이터 웨어하우스의 강점과 클라우드의 유연성 및 확장성을 어떻게 결합하는지를 중점적으로 다룹니다. 가상의 소매업체(Vintage Audio Co.)를 대상으로 엔드투엔드 작업을 수행하면서, 워크스페이스를 탐험하고, 거버넌스가 적용된 Unity Catalog 테이블을 쿼리하며, 분석 읽기를 위해 Unity Catalog 관리형 테이블을 빠르게 유지하고, Auto Loader로 데이터를 증분 로드하고, 스타 스키마를 모델링하며, Unity Catalog 메트릭 뷰를 통해 일관된 인사이트를 제공합니다. 이 모든 작업은 AI 기반 기능(Predictive Optimization, Genie Code)이 전반에 걸쳐 내장된 단일 거버넌스 환경에서 이루어집니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31904","entityUrl":{"path":"/kr/training/catalog/data-governance-at-scale-korean-6427"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-governance-at-scale-korean-6427"}}],"nid":31904,"vid":249941,"title":"Data Governance at Scale - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Unity Catalog를 사용하여 Databricks에서 스케일에 맞는 데이터 거버넌스를 구현하는 방법을 학습합니다. 속성 기반 액세스 제어, 관찰 가능성, 페더레이션 공유에 중점을 두며, 거버넌스가 적용된 태그로 ABAC를 구성하고, 레거시 세분화 제어에서 마이그레이션하고, 감사 및 비용 모니터링을 위한 시스템 테이블을 활성화 및 사용하고, 데이터 및 모델 품질을 위한 데이터 품질 모니터링을 배포하고, 영향 분석 및 규정 준수를 위한 리니지를 해석하고, 안전한 크로스 클라우드 협업을 위한 페더레이션 거버넌스 및 Delta Sharing 패턴을 적용합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31860","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6400"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-end-to-end-korean-6400"}}],"nid":31860,"vid":249269,"title":"Get Started with Databricks: End to End - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 포괄적인 실습 입문 과정입니다. 워크스페이스에서 시작하여 AI 및 머신 러닝 소개로 마무리되는 하나의 엔드투엔드 여정을 따라가며, Databricks에서 데이터를 다루는 데 필요한 일상적인 기술을 습득합니다.
이 과정에서 다루는 내용:
• Databricks 워크스페이스 탐색, compute 옵션, Lakehouse와 Genie 경험 비교.
• Unity Catalog를 통한 데이터 이해 및 수집(파일 업로드 및 카탈로그 탐색기 포함).
• Databricks Notebooks에서 작업하고 Genie Code를 활용하여 코드 작성 및 디버깅.
• SQL로 데이터 쿼리, 저장된 쿼리 관리, 대시보드 및 시각화 구축.
• Genie Agents를 활용한 자연어 기반 데이터 탐색.
• MLflow 및 Data Science Agent를 활용한 AI 및 머신 러닝 소개.
이 과정을 마치면 Databricks 탐색, Unity Catalog에서 데이터 검색 및 거버넌스, AI 지원을 통한 SQL 및 노트북 코드 작성, 대시보드 구축, Genie를 활용한 데이터 탐색에 익숙해질 것입니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31806","entityUrl":{"path":"/kr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-korean-3429"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-korean-3429"}}],"nid":31806,"vid":248575,"title":"Get Started with SQL Analytics and BI on Databricks - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform과 데이터 분석가가 일상적인 SQL 분석 및 BI 작업에 필요한 핵심 역량을 소개합니다. 워크스페이스와 Unity Catalog를 탐색하고, Serverless SQL Warehouse에서 Unity Catalog 관리 테이블에 대한 SQL 쿼리를 작성하며, Genie Code를 활용하여 SQL을 생성하고 디버깅하고, Delta Lake(DML, 버전 이력, 시간 여행, 복원)를 다루고, AI/BI Dashboards를 구축 및 게시하며, 대화형 분석을 위한 Genie Agents를 생성합니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31807","entityUrl":{"path":"/kr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-korean-3430"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-korean-3430"}}],"nid":31807,"vid":248576,"title":"Get Started with SQL Analytics and BI on Databricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform과 데이터 분석가가 일상적인 SQL 분석 및 BI 작업에 필요한 핵심 역량을 소개합니다. 워크스페이스와 Unity Catalog를 탐색하고, Serverless SQL Warehouse에서 Unity Catalog 관리 테이블에 대한 SQL 쿼리를 작성하며, Genie Code를 활용하여 SQL을 생성하고 디버깅하고, Delta Lake(DML, 버전 이력, 시간 여행, 복원)를 다루고, AI/BI Dashboards를 구축 및 게시하며, 대화형 분석을 위한 Genie Agents를 생성합니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31033","entityUrl":{"path":"/kr/training/catalog/building-agentic-applications-on-databricks-korean-6058"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-agentic-applications-on-databricks-korean-6058"}}],"nid":31033,"vid":246065,"title":"Building Agentic Applications on Databricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks에서 프로덕션급 에이전틱 애플리케이션을 구축하는 방법을 학습합니다. 학습자는 Unity Catalog와 MCP를 사용하여 거버넌스가 적용되는 에이전트 도구를 만들고, OpenAI Agents SDK로 단일 및 멀티 에이전트 시스템을 구축하며, supervisor agent가 오케스트레이션하는 Knowledge Assistant 사용 사례에 Agent Bricks와 Genie를 활용하는 방법을 배웁니다. 이 과정은 도구 프로토타이핑부터 프로덕션 배포까지 전체 단계를 다루며, MLflow tracing을 사용하여 에이전트 실행을 관찰하는 실습 경험을 제공합니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 SCORM 창을 반드시 닫아 주세요. ‘다음 레슨’ 버튼을 클릭하지 마세요. 클릭하면 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31034","entityUrl":{"path":"/kr/training/catalog/building-agentic-applications-on-databricks-korean-6059"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-agentic-applications-on-databricks-korean-6059"}}],"nid":31034,"vid":246066,"title":"Building Agentic Applications on Databricks - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks에서 프로덕션급 에이전틱 애플리케이션을 구축하는 방법을 학습합니다. 학습자는 Unity Catalog와 MCP를 사용하여 거버넌스가 적용되는 에이전트 도구를 만들고, OpenAI Agents SDK로 단일 및 멀티 에이전트 시스템을 구축하며, supervisor agent가 오케스트레이션하는 Knowledge Assistant 사용 사례에 Agent Bricks와 Genie를 활용하는 방법을 배웁니다. 이 과정은 도구 프로토타이핑부터 프로덕션 배포까지 전체 단계를 다루며, MLflow tracing을 사용하여 에이전트 실행을 관찰하는 실습 경험을 제공합니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 SCORM 창을 반드시 닫아 주세요. ‘다음 레슨’ 버튼을 클릭하지 마세요. 클릭하면 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30999","entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-6232"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-6232"}}],"nid":30999,"vid":245916,"title":"SQL Programming and Procedural Logic - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks 내에서 핵심 SQL 프로그래밍 및 절차적 로직 기술을 탐색하며, 모듈화되고 유지 관리 가능하며 프로덕션 준비가 완료된 분석 워크플로를 구축하는 방법에 중점을 둡니다. Common Table Expressions(고급 재귀 CTE 포함), 임시 뷰 및 테이블과 같은 세션 범위 객체, User Defined Functions와 같은 주요 SQL 구문을 학습하여 SQL 개발을 더 깔끔하고 재사용 가능하게 만드는 방법부터 시작합니다. 그런 다음 복합 문, 변수, 제어 흐름, 조건문, 루프 및 강력한 오류 처리를 사용하는 고급 SQL 스크립팅 기법을 통해 구조화되고 유연한 SQL 프로세스를 생성하는 방법을 안내받습니다. 또한 ACID 준수 다중 문 트랜잭션을 사용하여 이러한 다단계 파이프라인 전반에 걸쳐 데이터 일관성을 보장하는 방법도 학습합니다. 마지막으로 로직을 SQL Stored Procedures로 캡슐화하고 Lakeflow Jobs 및 마이그레이션 전략으로 복잡한 워크플로를 오케스트레이션하여 레거시 작업을 Databricks 플랫폼의 전체 기능을 활용하는 모듈화된 자동화 파이프라인으로 전환하는 방법을 알아봅니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 반드시 SCORM 창을 닫아 주세요. 'Next Lesson' 버튼을 클릭하지 마세요. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31000","entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-6234"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-6234"}}],"nid":31000,"vid":245917,"title":"SQL Programming and Procedural Logic - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks 내에서 핵심 SQL 프로그래밍 및 절차적 로직 기술을 탐색하며, 모듈화되고 유지 관리 가능하며 프로덕션 준비가 완료된 분석 워크플로를 구축하는 방법에 중점을 둡니다. Common Table Expressions(고급 재귀 CTE 포함), 임시 뷰 및 테이블과 같은 세션 범위 객체, User Defined Functions와 같은 주요 SQL 구문을 학습하여 SQL 개발을 더 깔끔하고 재사용 가능하게 만드는 방법부터 시작합니다. 그런 다음 복합 문, 변수, 제어 흐름, 조건문, 루프 및 강력한 오류 처리를 사용하는 고급 SQL 스크립팅 기법을 통해 구조화되고 유연한 SQL 프로세스를 생성하는 방법을 안내받습니다. 또한 ACID 준수 다중 문 트랜잭션을 사용하여 이러한 다단계 파이프라인 전반에 걸쳐 데이터 일관성을 보장하는 방법도 학습합니다. 마지막으로 로직을 SQL Stored Procedures로 캡슐화하고 Lakeflow Jobs 및 마이그레이션 전략으로 복잡한 워크플로를 오케스트레이션하여 레거시 작업을 Databricks 플랫폼의 전체 기능을 활용하는 모듈화된 자동화 파이프라인으로 전환하는 방법을 알아봅니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 반드시 SCORM 창을 닫아 주세요. 'Next Lesson' 버튼을 클릭하지 마세요. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30885","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6202"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-apps-korean-6202"}}],"nid":30885,"vid":245269,"title":"Get Started with Databricks Apps - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 개발자가 Databricks 플랫폼에서 직접 안전한 데이터 및 AI 애플리케이션을 빌드하고 배포할 수 있도록 지원하는 기능인 Databricks Apps를 소개합니다. 이 과정은 주로 조직 내 비기술 사용자가 데이터 인사이트에 접근할 수 있도록 맞춤형 애플리케이션을 만들어야 하는 데이터 과학자, 데이터 엔지니어 및 개발자를 대상으로 합니다.
이 과정은 Databricks Apps의 주요 구성 요소에 대한 개요를 제공하는 것으로 시작하며, 이후 외부 서비스 및 Databricks 리소스와 통합되는 간단한 앱을 배포하는 내용으로 이어집니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30847","entityUrl":{"path":"/kr/training/catalog/building-rag-agents-with-agent-bricks-korean-6033"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-rag-agents-with-agent-bricks-korean-6033"}}],"nid":30847,"vid":244640,"title":"Building RAG Agents with Agent Bricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Agent Bricks를 사용하여 검색 에이전트를 구축하는 실습 교육을 제공합니다. 참가자는 Knowledge Assistant를 살펴보고 쿼리하며, AI Functions를 사용하여 비정형 문서를 정형 데이터로 파싱하고, 의미 기반 검색을 위해 텍스트를 청킹하고, AI Search 인덱스를 구축하며, 여러 지식 소스를 기반으로 프로덕션에 사용할 수 있는 Knowledge Assistant를 생성하는 방법을 배웁니다.
참고: SCORM 강의 파일의 경우, 콘텐츠를 완료한 후 SCORM 창을 반드시 닫아 주세요. ‘다음 레슨’ 버튼을 클릭하지 마세요. 클릭하면 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
이 입문 과정에서는 Databricks Lakebase를 소개합니다. Lakebase는 Databricks Data Intelligence Platform에 내장된 완전 관리형 PostgreSQL 서비스로, 운영(OLTP) 및 분석(OLAP) 워크로드를 보다 긴밀하게 통합합니다.
이 과정은 OLTP와 OLAP 시스템을 비교하는 개념 강의로 시작하며, 각 시스템의 성능 특성, 스토리지 모델, 일반적인 사용 사례를 설명합니다. 또한 별도의 트랜잭션 데이터베이스와 분석 플랫폼을 유지 관리할 때 조직이 직면하는 데이터 이동, 지연 시간, 아키텍처 복잡성 등의 과제도 탐험합니다.
이어서 Databricks Lakebase가 이러한 과제를 해결하는 방법을 학습합니다. Lakebase는 Databricks Lakehouse와 직접 통합되는 PostgreSQL 호환 운영 데이터베이스를 제공하여, 운영 애플리케이션과 분석을 단일 통합 플랫폼 내에서 함께 활용할 수 있도록 지원합니다.
실습 랩을 통해 다음을 수행합니다:
Autoscaling compute를 사용하여 Lakebase 프로젝트를 생성하고 탐험합니다
• 브랜칭, 모니터링, 구성 설정을 포함한 Lakebase UI를 탐색합니다
• Lakebase SQL Editor를 사용하여 테이블을 생성하고 쿼리합니다
• Lakehouse Federation 및 외부 카탈로그를 사용하여 Databricks에서 Lakebase 데이터를 쿼리합니다
• Delta 테이블을 Lakebase에 동기화하여 Reverse ETL을 수행합니다
• Python에서 Lakebase에 연결하고 기본 CRUD 운영을 수행합니다
이 과정은 입문 과정이므로, Lakebase 작업을 위한 핵심 개념과 기본 워크플로우 이해에 중점을 둡니다. Lakebase를 기반으로 한 완전한 생산 애플리케이션 구축은 이 과정의 범위를 벗어납니다.
과정을 마치면, Lakebase가 Unity Catalog와 Databricks Lakehouse를 기반으로 하는 단일 거버넌스 플랫폼 내에서 운영 시스템과 분석을 어떻게 연결하는지 이해하게 됩니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30697","entityUrl":{"path":"/kr/training/catalog/introduction-to-python-for-data-science-and-data-engineering-korean-6114"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/introduction-to-python-for-data-science-and-data-engineering-korean-6114"}}],"nid":30697,"vid":239717,"title":"Introduction to Python for Data Science and Data Engineering - Korean","price":"1500.00","duration":57600,"body":{"processed":"이 과정은 Python을 처음 접하는 완전한 초보자를 대상으로 하며, 데이터를 프로그래밍 방식으로 다루는 기초를 제공합니다. 과정은 프로그래밍 표현식, 변수, 데이터 타입에 대한 기본 소개로 시작합니다. 이후 조건문 및 제어문, 함수, 컬렉션 타입, 반복문, 오류 처리, 클래스로 이어집니다. 외부 라이브러리를 활용하여 Python을 확장하는 방법을 배우고, 데이터 분석 및 시각화를 위한 Pandas 라이브러리 사용 경험을 쌓게 되며, Apache Spark를 활용한 Pandas Workflows 확장도 포함됩니다. 마지막으로 클라우드 컴퓨팅의 기본 개념을 탐험합니다. 과정 전반에 걸쳐 실습 과제를 통해 실습으로 넘어갑니다, 수업 이후에도 프로그래밍 지식을 심화할 수 있는 추가 리소스도 제공됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30661","entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-6091"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-6091"}}],"nid":30661,"vid":239024,"title":"Lakebase App Integration and Management - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Apps를 Databricks의 완전 관리형 클라우드 네이티브 PostgreSQL 플랫폼인 Lakebase와 통합하여 안전하고 엔터프라이즈에 적합한 애플리케이션 워크플로를 구축하는 방법을 배웁니다. Databricks Apps와 Lakebase에 대한 기초 지식을 바탕으로, 이 과정은 PostgreSQL 기초, Lakebase Autoscaling, 안전한 SQL 사용법, 안전한 연결 관리, 역할 기반 액세스, Data API 통합, 브랜치 기반 개발에 중점을 둡니다. 또한 AppKit이 이 워크플로 내에서 애플리케이션 개발을 어떻게 가속화하여 통합 개념에서 구현으로 더 효율적으로 나아갈 수 있도록 돕는지도 살펴봅니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30662","entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-6093"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-6093"}}],"nid":30662,"vid":239025,"title":"Lakebase App Integration and Management - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks Apps를 Databricks의 완전 관리형 클라우드 네이티브 PostgreSQL 플랫폼인 Lakebase와 통합하여 안전하고 엔터프라이즈에 적합한 애플리케이션 워크플로를 구축하는 방법을 배웁니다. Databricks Apps와 Lakebase에 대한 기초 지식을 바탕으로, 이 과정은 PostgreSQL 기초, Lakebase Autoscaling, 안전한 SQL 사용법, 안전한 연결 관리, 역할 기반 액세스, Data API 통합, 브랜치 기반 개발에 중점을 둡니다. 또한 AppKit이 이 워크플로 내에서 애플리케이션 개발을 어떻게 가속화하여 통합 개념에서 구현으로 더 효율적으로 나아갈 수 있도록 돕는지도 살펴봅니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"30612","entityUrl":{"path":"/kr/training/catalog/lakehouse-architecture-fundamentals-korean-6077"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/lakehouse-architecture-fundamentals-korean-6077"}}],"nid":30612,"vid":238738,"title":"Lakehouse Architecture Fundamentals - Korean","price":"0.00","duration":3600,"body":{"processed":"The Data Lakehouse For Dummies를 기반으로 한 개념 수준의 과정입니다. 학습자가 \"레이크하우스가 무엇인지 잘 모르는\" 상태에서 레이크하우스 아키텍처와 그 기반 기술에 대해 실질적인 대화를 나눌 수 있는 수준으로 나아갈 수 있도록 합니다. 레거시 아키텍처의 한계, 레이크하우스의 정의, 핵심 기술, 그리고 Databricks에서 데이터 인텔리전스와 통합 워크로드를 가능하게 하는 방법을 다룹니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30442","entityUrl":{"path":"/kr/training/catalog/answering-business-questions-with-databricks-genie-korean-6024"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/answering-business-questions-with-databricks-genie-korean-6024"}}],"nid":30442,"vid":237592,"title":"Answering Business Questions with Databricks Genie - Korean","price":"0.00","duration":7200,"body":{"processed":"이 강의에서는 Databricks Genie라는 대화형 분석 도구를 소개합니다. 이 도구를 사용하면 조직의 데이터에 대해 일상 언어로 질문을 하고, 관리되고 안전한 답변을 받을 수 있습니다. Genie Space가 무엇인지, 데이터가 어떻게 안전하게 보호되는지, 그리고 최상의 결과를 얻기 위한 모범 사례를 배우게 됩니다. 강의는 비즈니스 문제를 조사하며 경쟁하는 실습 게임을 통해 마무리됩니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30374","entityUrl":{"path":"/kr/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-korean-6010"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-korean-6010"}}],"nid":30374,"vid":237080,"title":"Building Semantic Models in Databricks with UC Metric Views - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 데이터 소비자가 귀하와 기업의 데이터 및 AI 팀의 부담을 줄이면서 검증된 비즈니스 인사이트를 얻을 수 있도록 지원하는 방법을 학습합니다. 골드 레이어 위에 시맨틱 레이어를 구축함으로써, 의사 결정자와 비즈니스 분석가가 핵심 비즈니스 성능 지표를 새로운 방식으로 탐험할 수 있는 기회를 제공하는 동시에, 효율적인 데이터 운영과 기업 검증 메트릭을 유지할 수 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30360","entityUrl":{"path":"/kr/training/catalog/generative-ai-engineering-with-databricks-korean-2827"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/generative-ai-engineering-with-databricks-korean-2827"}}],"nid":30360,"vid":236977,"title":"Generative AI Engineering with Databricks - Korean","price":"1500.00","duration":57600,"body":{"processed":"본 과정은 최신의 가장 인기 있는 프레임워크와 Databricks 기능을 사용하여 생성형 AI 애플리케이션을 구축하려는 데이터 과학자, 머신러닝 엔지니어 및 기타 데이터 실무자를 대상으로 합니다.
참고: Databricks Academy는 Databricks 환경 내 강의실 세션을 노트북 기반 형식으로 전환하고 있으며, 강의에 슬라이드 덱 사용을 중단합니다. 강의 노트북은 Vocareum 실습 환경에서 이용할 수 있습니다.
아래에서는 본 과정에 포함된 네 개의 4시간 모듈을 각각 설명합니다.
Building RAG Agents with Agent Bricks: 본 과정에서는 Databricks Agent Bricks를 사용하여 검색 에이전트를 구축하기 위한 실습 교육을 제공합니다. 참가자는 Knowledge Assistants를 탐색하고 쿼리하며, AI Functions를 사용하여 비정형 문서를 정형 데이터로 파싱하고, 시맨틱 검색을 위해 텍스트를 청크로 나누며, Vector Search 인덱스를 구축하고, 여러 지식 소스를 기반으로 하는 프로덕션 준비된 Knowledge Assistants를 생성하는 방법을 학습합니다.
Building Agentic Applications on Databricks: 본 과정에서는 학생들이 Databricks에서 프로덕션 등급의 에이전트 애플리케이션을 구축하는 방법을 학습합니다. 학생들은 Unity Catalog와 MCP를 사용하여 거버넌스된 에이전트 도구를 생성하고, OpenAI Agents SDK로 단일 및 다중 에이전트 시스템을 구축하며, 슈퍼바이저 에이전트로 오케스트레이션되는 knowledge assistant 사용 사례를 위해 Agent Bricks와 Genie를 활용하는 방법을 학습합니다. 본 과정은 도구 프로토타이핑부터 프로덕션 배포까지의 전체 진행 과정을 다루며, MLflow 트레이싱을 사용하여 에이전트 실행을 관찰하는 실습 경험을 제공합니다.
Agent Evaluation on Databricks: 본 과정에서는 학생들이 MLflow의 평가 프레임워크를 사용하여 AI 에이전트를 체계적으로 평가하는 방법을 학습하며, 기존 소프트웨어 테스트로는 처리할 수 없는 비결정론적 AI 시스템의 고유한 과제를 다룹니다. 학생들은 정확성 및 안전성과 같은 일반적인 기준을 위한 기본 내장 심사위원(built-in judges), 비즈니스별 요구 사항을 위한 가이드라인 심사위원, 특수한 요구 사항을 위한 맞춤형 심사위원 등 다양한 평가 접근 방식을 구현하는 방법을 학습합니다. 본 과정은 큐레이션된 데이터셋을 사용하는 오프라인 평가와 온라인 프로덕션 모니터링을 모두 다루며, MLflow의 트레이싱 기능을 사용하여 에이전트 실행 패턴을 이해하고 다양한 유형의 이해관계자로부터 인간 피드백을 수집하는 실습 경험을 제공합니다. 실용적인 데모와 랩을 통해 학생들은 AI 에이전트 개발 수명 주기 전반에 걸쳐 지속적인 품질 개선을 이끄는 평가 워크플로를 만드는 기술을 개발합니다.
Deploying and Monitoring Agent Applications on Databricks: 본 과정에서는 Databricks에서 생성형 AI 에이전트를 배포하고 모니터링하기 위한 엔드투엔드 수명 주기를 다룹니다. 참가자는 Declarative Automation Bundles(DABs)를 사용하여 에이전트를 Databricks Apps로 배포하고, Model Context Protocol(MCP)을 통해 도구를 통합하며, MLflow Tracing으로 에이전트를 계측하고, 스코어러, 멀티턴 심사위원 및 온라인 평가를 사용하여 프로덕션 품질을 평가하는 방법을 학습합니다. 실습 데모와 랩을 통해 참가자는 Databricks 플랫폼에서 프로덕션 등급의 AI 에이전트를 구축, 관찰 및 모니터링하는 실용적인 경험을 얻습니다.
Languages Available: English | 日本語 | Português BR | 한국어
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참고: Databricks Academy는 Databricks 환경 내 강의실 세션을 노트북 기반 형식으로 전환하고 있으며, 강의에 슬라이드 덱 사용을 중단합니다. 강의 노트북은 Vocareum 실습 환경에서 이용할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-23T09:00:00"},"endDate":{"value":"2026-10-23T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"30307","entityUrl":{"path":"/kr/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-korean-5968"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-korean-5968"}}],"nid":30307,"vid":236667,"title":"Deploying and Monitoring Agent Applications on Databricks - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks에서 생성형 AI 에이전트를 배포하고 모니터링하는 엔드투엔드 수명 주기를 다룹니다. 참가자는 Declarative Automation Bundles(DABs)를 사용하여 에이전트를 Databricks Apps로 배포하고, Model Context Protocol(MCP)을 통해 도구를 통합하고, MLflow Tracing으로 에이전트를 계측하며, scorer, 멀티턴 judge 및 온라인 평가를 사용하여 프로덕션 품질을 평가하는 방법을 배웁니다. 실습 데모와 실습을 통해 Databricks 플랫폼에서 프로덕션급 AI 에이전트를 구축하고 관찰하고 모니터링하는 실무 경험을 쌓습니다.
참고: Databricks Academy는 Databricks 환경 내 강의실 세션을 노트북 기반 형식으로 전환하고 있으며, 강의에 슬라이드 덱 사용을 중단합니다. 강의 노트북은 Vocareum 실습 환경에서 이용할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-29T09:00:00"},"endDate":{"value":"2026-10-29T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"30296","entityUrl":{"path":"/kr/training/catalog/building-rag-agents-with-agent-bricks-korean-5953"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-rag-agents-with-agent-bricks-korean-5953"}}],"nid":30296,"vid":236630,"title":"Building RAG Agents with Agent Bricks - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks Agent Bricks를 사용하여 검색 에이전트를 구축하는 실습 교육을 제공합니다. 참가자는 Knowledge Assistant를 살펴보고 쿼리하며, AI Functions를 사용하여 비정형 문서를 정형 데이터로 파싱하고, 의미 기반 검색을 위해 텍스트를 청킹하고, AI Search 인덱스를 구축하며, 여러 지식 소스를 기반으로 프로덕션에 사용할 수 있는 Knowledge Assistant를 생성하는 방법을 배웁니다.
참고: Databricks Academy는 Databricks 환경 내 교실 세션에서 노트북 기반 형식으로 전환하고 있으며, 강의용 슬라이드 덱의 사용을 중단하고 있습니다. Vocareum 실습 환경에서 강의 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-21T09:00:00"},"endDate":{"value":"2026-10-21T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"29804","entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4199"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4199"}}],"nid":29804,"vid":234772,"title":"AI/BI for Data Analysts - Korean","price":"75.00","duration":10800,"body":{"processed":"이 코스에서는 데이터 분석가가 Databricks에서 AI/BI Dashboards를 설계, 구축, 게시 및 운영하는 방법을 배웁니다. AI/BI Dashboards는 거버넌스가 적용된 Unity Catalog 데이터를 대화형 시각화, 필터, Genie 통합과 결합하여, 비즈니스 사용자가 코드를 작성하지 않고도 답을 탐색할 수 있게 합니다.
이 코스는 하나의 엔드 투 엔드 구축을 따라 진행됩니다. Unity Catalog의 소스 테이블에서 시작하여, 게시되고 모니터링되는 여러 페이지 대시보드로 마무리합니다. 그 과정에서 대시보드가 더 넓은 Databricks AI/BI 제품군에서 어떻게 자리매김하는지, 그리고 Genie, 데이터 세트, 시각화, 필터가 각각 워크플로의 어디에 들어맞는지 배웁니다.
다루는 내용은 다음과 같습니다.
• AI/BI Dashboards의 기초와, 그것이 Genie 및 Databricks 플랫폼의 나머지 요소와 어떻게 관련되는지.
• Unity Catalog에서 소스 데이터를 탐색하고 SQL로 재사용 가능한 대시보드 데이터 세트를 설계하기.
• 시각화(KPI, 추세, 세부 분석) 작성 및 깔끔한 여러 페이지 대시보드 구성.
• Genie Code를 사용하여 자연어 프롬프트로부터 SQL, 차트, 필터의 초안을 작성하기.
• 필터를 추가하여 대시보드를 대화형으로 만들고 보는 사람의 질문에 응답하도록 하기.
• 적절한 사람이 대시보드를 보고 편집할 수 있도록 게시, 공유, 권한 관리하기.
• 예약된 새로 고침, 캐싱, 사용량 모니터링과 함께 대시보드를 프로덕션에서 운영하기.
코스를 마칠 무렵에는 비즈니스 질문에서 출발하여, 이를 뒷받침하는 데이터 세트를 설계하고, 완성도 높은 대시보드를 구축하며, 올바른 권한과 정확성을 유지하는 새로 고침 전략과 함께 대상에게 제공할 수 있게 됩니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29805","entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4200"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4200"}}],"nid":29805,"vid":234773,"title":"AI/BI for Data Analysts - Korean","price":"0.00","duration":7200,"body":{"processed":"이 코스에서는 데이터 분석가가 Databricks에서 AI/BI Dashboards를 설계, 구축, 게시 및 운영하는 방법을 배웁니다. AI/BI Dashboards는 거버넌스가 적용된 Unity Catalog 데이터를 대화형 시각화, 필터, Genie 통합과 결합하여, 비즈니스 사용자가 코드를 작성하지 않고도 답을 탐색할 수 있게 합니다.
이 코스는 하나의 엔드 투 엔드 구축을 따라 진행됩니다. Unity Catalog의 소스 테이블에서 시작하여, 게시되고 모니터링되는 여러 페이지 대시보드로 마무리합니다. 그 과정에서 대시보드가 더 넓은 Databricks AI/BI 제품군에서 어떻게 자리매김하는지, 그리고 Genie, 데이터 세트, 시각화, 필터가 각각 워크플로의 어디에 들어맞는지 배웁니다.
다루는 내용은 다음과 같습니다.
• AI/BI Dashboards의 기초와, 그것이 Genie 및 Databricks 플랫폼의 나머지 요소와 어떻게 관련되는지.
• Unity Catalog에서 소스 데이터를 탐색하고 SQL로 재사용 가능한 대시보드 데이터 세트를 설계하기.
• 시각화(KPI, 추세, 세부 분석) 작성 및 깔끔한 여러 페이지 대시보드 구성.
• Genie Code를 사용하여 자연어 프롬프트로부터 SQL, 차트, 필터의 초안을 작성하기.
• 필터를 추가하여 대시보드를 대화형으로 만들고 보는 사람의 질문에 응답하도록 하기.
• 적절한 사람이 대시보드를 보고 편집할 수 있도록 게시, 공유, 권한 관리하기.
• 예약된 새로 고침, 캐싱, 사용량 모니터링과 함께 대시보드를 프로덕션에서 운영하기.
코스를 마칠 무렵에는 비즈니스 질문에서 출발하여, 이를 뒷받침하는 데이터 세트를 설계하고, 완성도 높은 대시보드를 구축하며, 올바른 권한과 정확성을 유지하는 새로 고침 전략과 함께 대상에게 제공할 수 있게 됩니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
이 과정에서는 Databricks Genie One을 소개합니다. Genie One은 AI 기반의 협업 환경으로, 여러분의 필요와 업무를 중심으로 설계되었습니다. 이를 통해 조직의 데이터에 대해 일반 언어로 질문하고 거버넌스가 적용된 안전한 답변을 받을 수 있으며, 보고서가 자동으로 실행되도록 일정을 설정하고, 워크플로를 자동화하여 더 빠르고 정확하게 더 많은 업무를 처리할 수 있습니다. 이는 여러분의 데이터와 비즈니스를 기반으로 하기 때문입니다. 이 과정에서는 Genie, Genie One, Genie Agents가 무엇인지, 데이터를 안전하게 보호하는 방법, 그리고 최상의 결과를 얻기 위한 모범 사례를 학습합니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29776","entityUrl":{"path":"/kr/training/catalog/catalog-management-and-data-organization-korean-5893"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/catalog-management-and-data-organization-korean-5893"}}],"nid":29776,"vid":234610,"title":"Catalog Management and Data Organization - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform에서 카탈로그 구조와 대규모 데이터 조직을 설계, 구현 및 거버넌스하는 방법을 학습합니다. 엔터프라이즈 레이크하우스의 중앙 집중식 거버넌스 계층으로서 Unity Catalog의 포괄적인 관점을 제공합니다. 5개 모듈로 나뉘어 있으며, Unity Catalog을 클라우드 배포 모델 내에 배치하는 것으로 시작하여 Account Console, metastore 생성 및 관리자 역할 계층 구조를 다룹니다. 그런 다음 명명 규칙, 소유권 패턴 및 MANAGE 위임을 사용하여 조직 토폴로지(사업부, 리전 및 개발/QA/프로덕션 환경)를 확장 가능한 카탈로그 및 스키마 설계로 변환합니다. 과정은 스토리지 자격 증명, 외부 위치, 관리 스토리지 계층 구조, 관리 대 외부 테이블 및 비테이블 데이터를 위한 UC Volumes와의 안전한 스토리지 통합을 다룹니다. 다음으로, 접근 패턴과 격리 전략 — 3단계 GRANT 체인, 워크스페이스-카탈로그 바인딩 및 스키마 수준 Attribute-Based Access Control (ABAC) 정책 — 을 적용하여 대규모 세분화된 데이터 보호를 시행합니다. 마지막으로, 과정은 카탈로그 설계, 자동화, 최소 권한 및 그룹 기반 접근 관리에 대한 모범 사례로 마무리됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29757","entityUrl":{"path":"/kr/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-korean-3739"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-korean-3739"}}],"nid":29757,"vid":234459,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI) - Korean","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
이 코스에서는 Databricks Data Intelligence Platform에서 기본적인 데이터 엔지니어링 워크플로를 수행하는 데 필요한 기초 기술을 소개합니다. 워크스페이스를 살펴보고, Unity Catalog를 사용하며, 데이터 엔지니어가 Databricks에서 일상적으로 활용하는 핵심 구성 요소를 학습합니다.
이 코스는 실습 중심으로 진행됩니다. 먼저 워크스페이스에 익숙해진 다음, 각 주제별로 데모와 랩 노트북을 짝지어 진행합니다. 데모에서는 강사 또는 가이드 노트북과 함께 개념을 살펴보고, 랩에서는 방금 학습한 내용을 직접 적용합니다.
Get Started with SQL Analytics and BI on Databricks
이 과정은 데이터 분석과 데이터 웨어하우징에 필수적인 기술을 다루는 Databricks Data Intelligence Platform을 소개합니다. 워크스페이스 탐색, 데이터 객체 다루기, SQL 쿼리 실행, Delta Lake 기능 사용, 대시보드 생성 등을 배우세요. 실습 실험은 실시간 Databricks 환경에서 실습 경험을 제공합니다.
Databricks Free Edition 계정 을 생성하여 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-30T13:00:00"},"endDate":{"value":"2026-10-30T17:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-11-20T13:00:00"},"endDate":{"value":"2026-11-20T17:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2027-01-22T13:00:00"},"endDate":{"value":"2027-01-22T17:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"29620","entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-5840"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/lakebase-app-integration-and-management-korean-5840"}}],"nid":29620,"vid":234126,"title":"Lakebase App Integration and Management - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks Apps를 Databricks의 완전 관리형 클라우드 네이티브 PostgreSQL 플랫폼인 Lakebase와 통합하여 안전하고 엔터프라이즈에 적합한 애플리케이션 워크플로를 구축하는 방법을 배웁니다. Databricks Apps와 Lakebase에 대한 기초 지식을 바탕으로, 이 과정은 PostgreSQL 기초, Lakebase Autoscaling, 안전한 SQL 사용법, 안전한 연결 관리, 역할 기반 액세스, Data API 통합, 브랜치 기반 개발에 중점을 둡니다. 또한 AppKit이 이 워크플로 내에서 애플리케이션 개발을 어떻게 가속화하여 통합 개념에서 구현으로 더 효율적으로 나아갈 수 있도록 돕는지도 살펴봅니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29628","entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-5858"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-5858"}}],"nid":29628,"vid":234134,"title":"Machine Learning Model Development - Korean","price":"0.00","duration":7200,"body":{"processed":"이 종합 강의는 Databricks에서 전통적인 머신러닝 모델을 개발하는 실용적인 가이드를 제공하며, 인기 있는 ML 라이브러리를 활용한 실습 시연과 워크플로우를 강조합니다. 참가자들은 회귀와 클러스터링 등 주요 ML 기법을 탐구하며 Databricks의 강력한 기능을 활용할 것입니다. 이 과정은 모델 추적을 위한 MLflow 통합, 특성 관리를 위한 Databricks Feature Store, 하이퍼파라미터 튜닝을 위한 Optuna를 다룹니다. 또한, 참가자들은 자연어, MCP 연결, 지침 및 기술을 활용해 전체 ML 수명 주기를 안내하는 Databricks의 AI 기반 코딩 어시스턴트인 Genie Code를 통해 모델 개발을 가속화하는 방법을 배우게 됩니다. 과정이 끝날 때에는 학습자들은 Databricks 환경에서 머신러닝 모델을 효율적으로 개발, 최적화, 배포할 수 있는 실용적인 기술과 실무 능력을 갖추게 됩니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"29629","entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-5859"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-5859"}}],"nid":29629,"vid":234135,"title":"Machine Learning Model Development - Korean","price":"75.00","duration":10800,"body":{"processed":"이 종합 강의는 Databricks에서 전통적인 머신러닝 모델을 개발하는 실용적인 가이드를 제공하며, 인기 있는 ML 라이브러리를 활용한 실습 시연과 워크플로우를 강조합니다. 참가자들은 회귀와 클러스터링 등 주요 ML 기법을 탐구하며 Databricks의 강력한 기능을 활용할 것입니다. 이 과정은 모델 추적을 위한 MLflow 통합, 특성 관리를 위한 Databricks Feature Store, 하이퍼파라미터 튜닝을 위한 Optuna를 다룹니다. 또한, 참가자들은 자연어, MCP 연결, 지침 및 기술을 활용해 전체 ML 수명 주기를 안내하는 Databricks의 AI 기반 코딩 어시스턴트인 Genie Code를 통해 모델 개발을 가속화하는 방법을 배우게 됩니다. 과정이 끝날 때에는 학습자들은 Databricks 환경에서 머신러닝 모델을 효율적으로 개발, 최적화, 배포할 수 있는 실용적인 기술과 실무 능력을 갖추게 됩니다."},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"29631","entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-5862"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/sql-programming-and-procedural-logic-korean-5862"}}],"nid":29631,"vid":234137,"title":"SQL Programming and Procedural Logic - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks 내에서 핵심 SQL 프로그래밍 및 절차적 로직 기술을 탐색하며, 모듈화되고 유지 관리 가능하며 프로덕션 준비가 완료된 분석 워크플로를 구축하는 방법에 중점을 둡니다. Common Table Expressions(고급 재귀 CTE 포함), 임시 뷰 및 테이블과 같은 세션 범위 객체, User Defined Functions와 같은 주요 SQL 구문을 학습하여 SQL 개발을 더 깔끔하고 재사용 가능하게 만드는 방법부터 시작합니다. 그런 다음 복합 문, 변수, 제어 흐름, 조건문, 루프 및 강력한 오류 처리를 사용하는 고급 SQL 스크립팅 기법을 통해 구조화되고 유연한 SQL 프로세스를 생성하는 방법을 안내받습니다. 또한 ACID 준수 다중 문 트랜잭션을 사용하여 이러한 다단계 파이프라인 전반에 걸쳐 데이터 일관성을 보장하는 방법도 학습합니다. 마지막으로 로직을 SQL Stored Procedures로 캡슐화하고 Lakeflow Jobs 및 마이그레이션 전략으로 복잡한 워크플로를 오케스트레이션하여 레거시 작업을 Databricks 플랫폼의 전체 기능을 활용하는 모듈화된 자동화 파이프라인으로 전환하는 방법을 알아봅니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29424","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-3463"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-3463"}}],"nid":29424,"vid":232501,"title":"Get Started with Databricks for Data Engineering - Korean","price":"75.00","duration":10800,"body":{"processed":"이 코스에서는 Databricks Data Intelligence Platform에서 기본적인 데이터 엔지니어링 워크플로를 수행하는 데 필요한 기초 기술을 소개합니다. 워크스페이스를 살펴보고, Unity Catalog를 사용하며, 데이터 엔지니어가 Databricks에서 일상적으로 활용하는 핵심 구성 요소를 학습합니다.
이 코스는 실습 중심으로 진행됩니다. 먼저 워크스페이스에 익숙해진 다음, 각 주제별로 데모와 랩 노트북을 짝지어 진행합니다. 데모에서는 강사 또는 가이드 노트북과 함께 개념을 살펴보고, 랩에서는 방금 학습한 내용을 직접 적용합니다.
다루는 내용은 다음과 같습니다.
• Databricks Data Intelligence Platform의 개요와 Databricks Workspace, Unity Catalog, 노트북이 어떻게 함께 작동하는지.
• Delta Lake 테이블의 생성 및 관리.
• INSERT, UPDATE, DELETE를 사용한 데이터 변경.
• Delta 테이블의 버전 기록 및 타임 트래블 살펴보기.
• Lakeflow Connect 옵션(CTAS, 업로드 UI, COPY INTO)을 사용한 데이터 수집.
• 브론즈, 실버, 골드 계층을 통해 데이터를 변환하는 메달리온 아키텍처 파이프라인 구축.
• Lakeflow Jobs를 사용한 파이프라인 자동화.
• (보너스) Spark Declarative Pipelines를 사용한 선언형 파이프라인 구축.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29425","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-3464"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-3464"}}],"nid":29425,"vid":232502,"title":"Get Started with Databricks for Data Engineering - Korean","price":"0.00","duration":7200,"body":{"processed":"이 코스에서는 Databricks Data Intelligence Platform에서 기본적인 데이터 엔지니어링 워크플로를 수행하는 데 필요한 기초 기술을 소개합니다. 워크스페이스를 살펴보고, Unity Catalog를 사용하며, 데이터 엔지니어가 Databricks에서 일상적으로 활용하는 핵심 구성 요소를 학습합니다.
이 코스는 실습 중심으로 진행됩니다. 먼저 워크스페이스에 익숙해진 다음, 각 주제별로 데모와 랩 노트북을 짝지어 진행합니다. 데모에서는 강사 또는 가이드 노트북과 함께 개념을 살펴보고, 랩에서는 방금 학습한 내용을 직접 적용합니다.
다루는 내용은 다음과 같습니다.
• Databricks Data Intelligence Platform의 개요와 Databricks Workspace, Unity Catalog, 노트북이 어떻게 함께 작동하는지.
• Delta Lake 테이블의 생성 및 관리.
• INSERT, UPDATE, DELETE를 사용한 데이터 변경.
• Delta 테이블의 버전 기록 및 타임 트래블 살펴보기.
• Lakeflow Connect 옵션(CTAS, 업로드 UI, COPY INTO)을 사용한 데이터 수집.
• 브론즈, 실버, 골드 계층을 통해 데이터를 변환하는 메달리온 아키텍처 파이프라인 구축.
• Lakeflow Jobs를 사용한 파이프라인 자동화.
• (보너스) Spark Declarative Pipelines를 사용한 선언형 파이프라인 구축.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29358","entityUrl":{"path":"/kr/training/catalog/building-enterprise-applications-with-databricks-apps-korean-5628"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-enterprise-applications-with-databricks-apps-korean-5628"}}],"nid":29358,"vid":230893,"title":"Building Enterprise Applications with Databricks Apps - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 개발자가 안전한 데이터 및 AI 애플리케이션을 Databricks 플랫폼에서 직접 구축하고 배포할 수 있도록 지원하는 새로운 기능인 Databricks Apps를 소개합니다. 주로 조직 내 비기술 사용자가 데이터 인사이트를 활용할 수 있는 맞춤형 애플리케이션을 만들어야 하는 데이터 과학자, 데이터 엔지니어, 개발자를 대상으로 합니다.
이 과정은 먼저 Databricks Apps의 주요 구성 요소에 대한 개요로 시작하여 외부 서비스와 통합되는 간단한 앱을 배포합니다. 다음으로 Databricks 플랫폼 기능과 통합되는 지능형 데이터 기반 애플리케이션을 구축하고 배포하는 방법을 배웁니다. 그런 다음 Databricks 환경 외부에서 앱을 개발하는 방법을 다룹니다. 마지막으로 안전하고 신뢰할 수 있는 엔터프라이즈 앱을 구현하기 위한 모범 사례를 자세히 살펴보며 마무리합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Español | française | Português BR
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29208","entityUrl":{"path":"/kr/training/catalog/building-reliable-conversational-agents-with-genie-korean-5567"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-reliable-conversational-agents-with-genie-korean-5567"}}],"nid":29208,"vid":229276,"title":"Building Reliable Conversational Agents with Genie - Korean","price":"750.00","duration":14400,"body":{"processed":"이 코스에서는 Databricks Genie Space를 설계, 구축, 유지 관리하는 방법을 배웁니다. Genie Space는 비즈니스 사용자가 거버넌스된 데이터에 대해 질문하고 코드를 작성하지 않고도 SQL 기반 답변을 받을 수 있는 자연어 인터페이스입니다.
Genie가 Databricks AI/BI 제품군에 어떻게 들어맞는지, 그리고 자연어를 어떻게 신뢰할 수 있는 SQL 쿼리로 변환하는지 배웁니다. 이 코스는 정확하고 일관되며 신뢰할 수 있는 결과를 제공하는 Genie Space를 만드는 데 무엇이 필요한지에 초점을 맞춥니다.
소스 데이터를 이해하고 벤치마크를 정의하는 것에서부터, Knowledge Store의 큐레이션 도구 전체를 사용해 Genie Space를 구성하고 개선하는 것까지, 완전한 엔드 투 엔드 워크플로를 따라갑니다. 이 도구에는 메타데이터, 동의어, 프롬프트 매칭, SQL 로직, 예시 쿼리, 텍스트 instructions가 포함됩니다.
또한 Databricks One을 통해 비즈니스 사용자와 Genie Space를 공유하는 방법, Unity Catalog 거버넌스가 어떻게 자동으로 적용되는지를 이해하고, 모니터링과 사용자 피드백을 사용해 시간이 지나면서 품질을 지속적으로 개선하는 방법을 배웁니다.
코스를 마칠 때쯤이면, 거버넌스되고 셀프서비스인 대화형 분석을 대규모로 제공하는, 생산 준비가 된 Genie Space를 만들고 관리할 수 있게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29069","entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5506"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5506"}}],"nid":29069,"vid":228098,"title":"Building ETL Pipelines with SQL - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에서 순수 SQL을 사용해 운영 준비가 된 ETL 파이프라인을 구축하는 방법을 가르칩니다. 학생들은 점진적 적재를 위한 Auto Loader가 포함된 스트리밍 테이블, 실버에서 골드로 변환을 위한 점진적 리프레시가 있는 Materialized Views, 선언적 SCD 타입 1 및 타입 2 차원 관리를 위한 AUTO CDC(FLOW AUTO CDC), 그리고 운영 오케스트레이션을 위한 SQL 파일 작업이 포함된 Lakeflow Jobs를 배웁니다. 이 과정은 메달리온 아키텍처(브론즈 → 실버 → 골드)를 통해 현실적인 소매 데이터셋을 따라갑니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29070","entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5512"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5512"}}],"nid":29070,"vid":228099,"title":"Building ETL Pipelines with SQL - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에서 순수 SQL을 사용해 운영 준비가 된 ETL 파이프라인을 구축하는 방법을 가르칩니다. 학생들은 점진적 적재를 위한 Auto Loader가 포함된 스트리밍 테이블, 실버에서 골드로 변환을 위한 점진적 리프레시가 있는 Materialized Views, 선언적 SCD 타입 1 및 타입 2 차원 관리를 위한 AUTO CDC(FLOW AUTO CDC), 그리고 운영 오케스트레이션을 위한 SQL 파일 작업이 포함된 Lakeflow Jobs를 배웁니다. 이 과정은 메달리온 아키텍처(브론즈 → 실버 → 골드)를 통해 현실적인 소매 데이터셋을 따라갑니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29029","entityUrl":{"path":"/kr/training/catalog/architecting-data-warehouses-for-large-scale-deployments-korean-5500"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/architecting-data-warehouses-for-large-scale-deployments-korean-5500"}}],"nid":29029,"vid":227795,"title":"Architecting Data Warehouses for Large-Scale Deployments - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 대규모 data warehousing 배포를 위한 성능 최적화, 비용 관리 및 보안을 다룹니다.
이 과정은 여러 사업부에 걸쳐 수백 또는 수천 명의 사용자에게 서비스를 제공하는 Databricks 환경을 관리하는 data warehousing 실무자를 위해 설계되었습니다. 높은 성능, 비용 효율성, 보안 표준 준수를 유지하면서 data warehousing 운영을 효율적으로 확장하는 데 필요한 기술을 습득하게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28955","entityUrl":{"path":"/kr/training/catalog/get-started-with-lakebase-korean-5456"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-lakebase-korean-5456"}}],"nid":28955,"vid":226436,"title":"Get Started with Lakebase - Korean","price":"75.00","duration":10800,"body":{"processed":"이 입문 과정에서는 Databricks Lakebase를 소개합니다. Lakebase는 Databricks Data Intelligence Platform에 내장된 완전 관리형 PostgreSQL 서비스로, 운영(OLTP) 및 분석(OLAP) 워크로드를 보다 긴밀하게 통합합니다.
이 과정은 OLTP와 OLAP 시스템을 비교하는 개념 강의로 시작하며, 각 시스템의 성능 특성, 스토리지 모델, 일반적인 사용 사례를 설명합니다. 또한 별도의 트랜잭션 데이터베이스와 분석 플랫폼을 유지 관리할 때 조직이 직면하는 데이터 이동, 지연 시간, 아키텍처 복잡성 등의 과제도 탐험합니다.
이어서 Databricks Lakebase가 이러한 과제를 해결하는 방법을 학습합니다. Lakebase는 Databricks Lakehouse와 직접 통합되는 PostgreSQL 호환 운영 데이터베이스를 제공하여, 운영 애플리케이션과 분석을 단일 통합 플랫폼 내에서 함께 활용할 수 있도록 지원합니다.
실습 랩을 통해 다음을 수행합니다:
Autoscaling compute를 사용하여 Lakebase 프로젝트를 생성하고 탐험합니다
• 브랜칭, 모니터링, 구성 설정을 포함한 Lakebase UI를 탐색합니다
• Lakebase SQL Editor를 사용하여 테이블을 생성하고 쿼리합니다
• Lakehouse Federation 및 외부 카탈로그를 사용하여 Databricks에서 Lakebase 데이터를 쿼리합니다
• Delta 테이블을 Lakebase에 동기화하여 Reverse ETL을 수행합니다
• Python에서 Lakebase에 연결하고 기본 CRUD 운영을 수행합니다
이 과정은 입문 과정이므로, Lakebase 작업을 위한 핵심 개념과 기본 워크플로우 이해에 중점을 둡니다. Lakebase를 기반으로 한 완전한 생산 애플리케이션 구축은 이 과정의 범위를 벗어납니다.
과정을 마치면, Lakebase가 Unity Catalog와 Databricks Lakehouse를 기반으로 하는 단일 거버넌스 플랫폼 내에서 운영 시스템과 분석을 어떻게 연결하는지 이해하게 됩니다.
참고: SCORM 강의 파일을 이용할 때는 콘텐츠를 모두 학습한 후 SCORM 창을 닫으시기 바랍니다. ‘다음 강의’ 버튼을 클릭하지 마십시오. 클릭할 경우 SCORM 모듈이 완료로 표시되지 않을 수 있습니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"28958","entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5465"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/building-etl-pipelines-with-sql-korean-5465"}}],"nid":28958,"vid":226439,"title":"Building ETL Pipelines with SQL - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform에서 순수 SQL을 사용하여 생산 준비가 완료된 ETL 파이프라인을 구축하는 방법을 학습합니다. 수강생은 증분 수집을 위한 Auto Loader를 활용한 Streaming 테이블, 실버에서 골드로의 변환을 위한 증분 갱신이 적용된 구체화된 뷰(Materialized Views), 선언적 SCD Type 1 및 Type 2 차원 관리를 위한 AUTO CDC(FLOW AUTO CDC), 그리고 데이터 품질 기대값, PRIVATE 테이블, 통합 모니터링을 갖춘 생산 다중 테이블 파이프라인으로 이러한 객체를 그룹화하는 Apache Spark Declarative Pipelines(SDP)를 학습합니다. 이 과정은 메달리온 아키텍처(브론즈 → 실버 → 골드)를 따라 실제 소매 데이터셋을 다룹니다. Lakeflow Jobs를 활용한 오케스트레이션은 보너스 모듈로 제공됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28886","entityUrl":{"path":"/kr/training/catalog/get-started-with-lakebase-korean-5454"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-lakebase-korean-5454"}}],"nid":28886,"vid":225782,"title":"Get Started with Lakebase - Korean","price":"0.00","duration":7200,"body":{"processed":"이 입문 과정에서는 Databricks Lakebase를 소개합니다. Lakebase는 Databricks Data Intelligence Platform에 내장된 완전 관리형 PostgreSQL 서비스로, 운영(OLTP) 및 분석(OLAP) 워크로드를 보다 긴밀하게 통합합니다.
이 과정은 OLTP와 OLAP 시스템을 비교하는 개념 강의로 시작하며, 각 시스템의 성능 특성, 스토리지 모델, 일반적인 사용 사례를 설명합니다. 또한 별도의 트랜잭션 데이터베이스와 분석 플랫폼을 유지 관리할 때 조직이 직면하는 데이터 이동, 지연 시간, 아키텍처 복잡성 등의 과제도 탐험합니다.
이어서 Databricks Lakebase가 이러한 과제를 해결하는 방법을 학습합니다. Lakebase는 Databricks Lakehouse와 직접 통합되는 PostgreSQL 호환 운영 데이터베이스를 제공하여, 운영 애플리케이션과 분석을 단일 통합 플랫폼 내에서 함께 활용할 수 있도록 지원합니다.
이 과정은 입문 과정이므로, Lakebase 작업을 위한 핵심 개념과 기본 워크플로우 이해에 중점을 둡니다. Lakebase를 기반으로 한 완전한 생산 애플리케이션 구축은 이 과정의 범위를 벗어납니다.
과정을 마치면, Lakebase가 Unity Catalog와 Databricks Lakehouse를 기반으로 하는 단일 거버넌스 플랫폼 내에서 운영 시스템과 분석을 어떻게 연결하는지 이해하게 됩니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28138","entityUrl":{"path":"/kr/training/catalog/introduction-to-apache-spark-korean-4313"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/introduction-to-apache-spark-korean-4313"}}],"nid":28138,"vid":217443,"title":"Introduction to Apache Spark™ - Korean","price":"750.00","duration":14400,"body":{"processed":"이 입문자 친화적인 과정에서는 대규모 데이터 처리를 위한 Apache Spark의 기본 개념을 다룹니다. Spark의 분산 아키텍처를 탐험하고, DataFrame API를 숙달하며, Python을 사용하여 데이터를 읽고, 쓰고, 처리하는 방법을 학습합니다. 실습 예제를 통해 Spark 변환 및 액션을 효율적으로 실행하는 데 필요한 기술을 습득합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-08T14:00:00"},"endDate":{"value":"2026-12-08T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28185","entityUrl":{"path":"/kr/training/catalog/databricks-accredited-platform-administrator-accreditation-korean-4652"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-accredited-platform-administrator-accreditation-korean-4652"}}],"nid":28185,"vid":217490,"title":"Databricks Accredited Platform Administrator Accreditation - Korean","price":"0.00","duration":900,"body":{"processed":"Databricks 공인 플랫폼 관리자 시험은 20분 동안 진행되는 비감독 인증 시험으로, Unity Catalog를 사용하여 Databricks Lakehouse 플랫폼을 관리 및 운영할 수 있는 지식을 평가합니다. 이 시험은 플랫폼 운영의 기본 사항 수행 능력, 신원 관리, 플랫폼 구성 및 보안 설정, 컴퓨팅 리소스 관리, 플랫폼 내 데이터 관리 및 보안 설정, 플랫폼 내 CI/CD 도구 운영 능력을 평가합니다. 시험에 합격한 응시자에게는 Databricks 공인 플랫폼 관리자 배지와 인증서가 수여됩니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28316","entityUrl":{"path":"/kr/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-korean-3019"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-korean-3019"}}],"nid":28316,"vid":217621,"title":"Advanced Techniques with Apache Spark Declarative Pipelines - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 생산 수준의 스트리밍 파이프라인을 구축하기 위한 Databricks의 Apache Spark Declarative Pipelines(SDP)를 살펴봅니다. 실제 레이크하우스 엔지니어링에 필수적인 고급 설계 패턴, 강력한 데이터 품질 적용, 그리고 크로스 플랫폼 통합에 대해 학습합니다.
과정 전반에 걸쳐 현대적인 데이터 수집 및 처리 기법을 심층적으로 다루며, 레이아웃 최적화를 위한 Liquid 클러스터링과 혼합 스키마 이벤트를 위한 멀티플렉스 스트리밍 패턴 등의 도구를 숙달합니다. 모듈을 마치면 스키마 진화를 자신 있게 처리하고, 변경 데이터 캡처(CDC)를 자동화하며, 데이터 무결성을 보장하는 방법을 습득하게 됩니다.
강의와 실습 데모를 통해 다음을 수행합니다:
• 다중 소스 데이터를 단일 브론즈 테이블로 수집하는 멀티 플로우 파이프라인을 구축합니다.
• 실버 및 골드 레이어 전반에 걸쳐 Liquid 클러스터링과 데이터 품질 Expectations를 적용합니다.
• 크로스 플랫폼 데이터 접근을 위해 Iceberg UniForm과 함께 멀티플렉스 패턴을 구현합니다.
• AUTO CDC INTO를 사용하여 SCD Type 2 이력 추적을 자동화합니다.
• 잘못된 레코드를 감사하고 관리하기 위한 데이터 무손실 격리 파이프라인을 설계합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
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Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-20T09:00:00"},"endDate":{"value":"2026-10-20T11:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28139","entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4319"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4319"}}],"nid":28139,"vid":217444,"title":"Developing Applications with Apache Spark - Korean","price":"750.00","duration":14400,"body":{"processed":"Apache Spark를 활용한 확장 가능한 데이터 처리를 이 과정에서 마스터하십시오. 효율적인 ETL 파이프라인을 구축하고, 고급 분석을 수행하며, Spark의 DataFrame API를 사용하여 분산 데이터 변환을 최적화하는 방법을 학습합니다. 그룹화, 집계, 조인, 집합 운영 및 윈도우 함수를 탐험합니다. 배열, 맵, 구조체와 같은 복잡한 데이터 유형을 다루면서 성능 최적화를 위한 모범 사례를 적용합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-10T14:00:00"},"endDate":{"value":"2026-12-10T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28204","entityUrl":{"path":"/kr/training/catalog/get-started-with-ai-agents-on-databricks-korean-4783"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-ai-agents-on-databricks-korean-4783"}}],"nid":28204,"vid":217509,"title":"Get Started with AI Agents on Databricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 AI 에이전트, 최신 AI 애플리케이션에서의 역할, Databricks Platform에서 AI 에이전트 애플리케이션을 구축하는 방법을 소개합니다. AI 에이전트의 원리, 기존 AI 시스템과의 차이점에 대해 배우고 주요 구성 요소를 탐색합니다. 대화형 데모와 실습을 통해 Mosaic AI 및 Agent Bricks를 사용하여 Databricks에서 AI 에이전트를 빌드, 배포 및 평가하는 방법을 볼 수 있습니다. 이 과정을 마치면 Databricks Data Intelligence Platform을 사용하여 AI 에이전트를 만들고 배포하는 방법을 이해하게 됩니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"28319","entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-3034"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/machine-learning-model-development-korean-3034"}}],"nid":28319,"vid":217624,"title":"Machine Learning Model Development - Korean","price":"750.00","duration":14400,"body":{"processed":"이 종합 과정은 Databricks에서 전통적인 머신 러닝 모델을 개발하기 위한 실용적인 가이드를 제공하며, 인기 있는 ML 라이브러리를 사용한 실습 데모 및 Workflows에 중점을 둡니다. 참가자들은 회귀 및 클러스터링을 포함한 핵심 ML 기법을 탐험하면서 Databricks의 강력한 기능을 활용하게 됩니다. 이 과정은 모델 추적을 위한 MLflow 통합, 특성 관리를 위한 Databricks Feature Store, 그리고 하이퍼파라미터 튜닝을 위한 Optuna를 다룹니다. 또한 참가자들은 자연어, MCP 연결, 지침 및 스킬을 활용하여 전체 ML 라이프사이클을 가이드하는 Databricks의 AI 기반 코딩 어시스턴트인 Genie Code를 통해 모델 개발을 가속화하는 방법을 학습합니다. 과정이 끝나면 학습자들은 Databricks 환경에서 머신 러닝 모델을 효율적으로 개발, 최적화 및 배포할 수 있는 실무 역량을 갖추게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28380","entityUrl":{"path":"/kr/training/catalog/data-analysis-with-databricks-korean-3494"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-analysis-with-databricks-korean-3494"}}],"nid":28380,"vid":217685,"title":"Data Analysis with Databricks - Korean","price":"1000.00","duration":28800,"body":{"processed":"이 교육 과정에서는 Databricks SQL에 대한 포괄적인 소개를 제공합니다. 학습자는 데이터를 수집하고, 쿼리를 작성하고, 시각화 및 대시보드를 만들고, 알림을 구성합니다. 이 과정을 통해 Databricks 공인 데이터 분석가 자격증 시험을 준비할 수 있습니다.
이 과정은 4시간짜리 두 개의 모듈로 구성됩니다.
SQL Analytics on Databricks
이 과정에서는 Databricks SQL에 특히 초점을 맞춰 Databricks를 사용하여 데이터 분석을 효과적으로 수행하는 방법을 학습합니다. Databricks 데이터 애널리스트로서 귀하의 책임에는 관련 데이터를 찾고, 잠재적인 응용 프로그램을 위해 데이터를 분석하고, 귀중한 비즈니스 통찰력을 제공하는 형식으로 데이터를 변환하는 것이 포함됩니다.
또한 Databricks Data Intelligence Platform에서 Notebooks, SQL Editor, Databricks SQL과 같은 도구를 사용하여 데이터 객체를 관리하는 역할과 이를 조작하는 방법을 이해하게 됩니다.
또한, 데이터 자산과 전반적인 플랫폼을 관리하는 데 있어 Unity Catalog의 중요성에 대해서도 알아봅니다. 마지막으로, 이 과정에서는 Databricks가 어떻게 성능 최적화를 용이하게 하는지에 대한 개요를 제공하고, Databricks에서 SQL 분석을 실행할 때 내부적으로 발생하는 프로세스를 이해하기 위해 Query Insights에 액세스하는 방법을 알려드립니다.
AI/BI for Data Analysts
이 코스에서는 데이터 분석가가 Databricks에서 AI/BI Dashboards를 설계, 구축, 게시 및 운영하는 방법을 배웁니다. AI/BI Dashboards는 거버넌스가 적용된 Unity Catalog 데이터를 대화형 시각화, 필터, Genie 통합과 결합하여, 비즈니스 사용자가 코드를 작성하지 않고도 답을 탐색할 수 있게 합니다.
이 코스는 하나의 엔드 투 엔드 구축을 따라 진행됩니다. Unity Catalog의 소스 테이블에서 시작하여, 게시되고 모니터링되는 여러 페이지 대시보드로 마무리합니다. 그 과정에서 대시보드가 더 넓은 Databricks AI/BI 제품군에서 어떻게 자리매김하는지, 그리고 Genie, 데이터 세트, 시각화, 필터가 각각 워크플로의 어디에 들어맞는지 배웁니다.
다루는 내용은 다음과 같습니다.
• AI/BI Dashboards의 기초와, 그것이 Genie 및 Databricks 플랫폼의 나머지 요소와 어떻게 관련되는지.
• Unity Catalog에서 소스 데이터를 탐색하고 SQL로 재사용 가능한 대시보드 데이터 세트를 설계하기.
• 시각화(KPI, 추세, 세부 분석) 작성 및 깔끔한 여러 페이지 대시보드 구성.
• Genie Code를 사용하여 자연어 프롬프트로부터 SQL, 차트, 필터의 초안을 작성하기.
• 필터를 추가하여 대시보드를 대화형으로 만들고 보는 사람의 질문에 응답하도록 하기.
• 적절한 사람이 대시보드를 보고 편집할 수 있도록 게시, 공유, 권한 관리하기.
• 예약된 새로 고침, 캐싱, 사용량 모니터링과 함께 대시보드를 프로덕션에서 운영하기.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28140","entityUrl":{"path":"/kr/training/catalog/stream-processing-and-analysis-with-apache-spark-korean-4339"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/stream-processing-and-analysis-with-apache-spark-korean-4339"}}],"nid":28140,"vid":217445,"title":"Stream Processing and Analysis with Apache Spark - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 Databricks에서 Spark Structured Streaming API를 사용하여 확장 가능하고 내결함성을 갖춘 스트림 처리 애플리케이션을 개발하는 방법을 학습자에게 안내합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 |한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-15T14:00:00"},"endDate":{"value":"2026-12-15T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28207","entityUrl":{"path":"/kr/training/catalog/data-governance-fundamentals-korean-4818"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-governance-fundamentals-korean-4818"}}],"nid":28207,"vid":217512,"title":"Data Governance Fundamentals - Korean","price":"0.00","duration":2700,"body":{"processed":"이 강의에서는 데이터 거버넌스와 Unity Catalog의 기본을 탐구하게 됩니다. 데이터 카탈로그의 진화와 목적, Unity Catalog의 아키텍처와 구성 요소, 그리고 거버넌스에서 데이터 품질, 보안, 규정 준수, 리니지, 감사의 중요성에 대해 배우게 됩니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28320","entityUrl":{"path":"/kr/training/catalog/machine-learning-model-deployment-korean-3036"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/machine-learning-model-deployment-korean-3036"}}],"nid":28320,"vid":217625,"title":"Machine Learning Model Deployment - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 세 가지 주요 머신 러닝 배포 전략을 소개하고 Databricks에서 각 전략의 구현 방법을 설명하도록 설계되었습니다. 모델 배포의 기본 사항을 탐색한 후, 배치 추론을 심층적으로 다루며 배치 추론 시나리오에서 모델을 활용하기 위한 실습 데모와 실습 과제를 제공하고, 성능 최적화에 대한 고려 사항도 함께 다룹니다. 과정의 두 번째 부분에서는 파이프라인 배포를 포괄적으로 다루며, 마지막 부분에서는 실시간 배포에 초점을 맞춥니다. 참가자들은 실습 데모와 실습 과제에 참여하여 Model Serving으로 모델을 배포하고 실시간 추론을 위해 서빙 엔드포인트를 활용하게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28388","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3521"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3521"}}],"nid":28388,"vid":217693,"title":"Get Started with Databricks for Machine Learning - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform을 사용하여 간단한 데이터 사이언스 및 머신 러닝 워크플로를 수행할 수 있는 기본 기술을 학습합니다. 워크스페이스에 대한 안내와 함께 Notebooks 사용 방법을 배웁니다. 탐색적 데이터 분석과 특성 엔지니어링을 탐험하고, MLflow를 사용하여 모델을 추적 및 관리하며, Databricks Genie Code를 활용한 실험을 진행하고, Databricks Model Serving으로 모델을 배포합니다. 마지막으로, 이 과정은 엔드투엔드 머신 러닝을 다루는 종합 실습을 통해 이러한 기술들을 하나로 통합합니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28141","entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4343"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4343"}}],"nid":28141,"vid":217446,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 안전한 데이터 거버넌스, 액세스 제어 및 계보 추적을 위한 Unity Catalog에 중점을 두고 확장 가능한 데이터 워크플로를 위한 레이크하우스 아키텍처 및 메달리온 설계를 살펴봅니다. 커리큘럼에는 Delta Lake를 사용하여 신뢰할 수 있는 ACID 호환 파이프라인 구축이 포함됩니다. 파티셔닝, 캐싱, 쿼리 튜닝과 같은 Spark 최적화 기술을 살펴보고 실제 문제를 해결하기 위한 효율적인 데이터 엔지니어링 및 분석을 위한 성능 모니터링, 문제 해결 및 모범 사례를 배웁니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28211","entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4831"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4831"}}],"nid":28211,"vid":217516,"title":"Get Started with Data Governance on Databricks - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 실습 데모와 캡스톤 랩을 통해 Databricks에서 Unity Catalog와 세분화된 액세스 제어를 탐험합니다. 테이블 유형, 카탈로그 및 스키마 구성, 그룹 기반 액세스 관리, 액세스 제어 마이그레이션 전략에 대해 학습합니다. 이 과정에는 행 수준 보안 및 열 마스킹을 사용한 세분화된 액세스 제어 적용, 속성 기반 액세스 제어, 제어 결합, 제어 마이그레이션에 관한 데모와 포괄적인 거버넌스 구현을 위한 랩이 포함되어 있습니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28321","entityUrl":{"path":"/kr/training/catalog/data-preparation-for-machine-learning-korean-3038"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-preparation-for-machine-learning-korean-3038"}}],"nid":28321,"vid":217626,"title":"Data Preparation for Machine Learning - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 Databricks를 사용하여 머신 러닝을 위한 데이터 준비의 기본 사항에 중점을 둡니다. 참가자들은 전통적인 머신 러닝 애플리케이션에 맞게 데이터를 탐색, 정제 및 구성하는 데 필요한 핵심 기술을 학습합니다. 주요 주제로는 데이터 시각화, 특성 엔지니어링, 최적의 특성 저장 전략이 포함됩니다. 실습 과제를 통해 참가자들은 Databricks 내에서 머신 러닝을 위한 데이터 세트를 효율적으로 준비하는 실무 경험을 쌓게 됩니다. 이 과정은 어소시에이트 수준의 데이터 과학자 및 머신 러닝 실무자, 그리고 데이터 준비 역량을 강화하고자 하는 개인을 대상으로 설계되었으며, 성공적인 머신 러닝 모델 배포를 위한 탄탄한 기반을 제공합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28393","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3572"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3572"}}],"nid":28393,"vid":217698,"title":"Get Started with Databricks for Machine Learning - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform을 활용하여 기본 머신러닝 워크플로를 실행하고 데이터 사이언스 워크로드를 지원하는 데 필요한 기초 기술을 습득하게 됩니다. 머신러닝 실무자의 관점에서 플랫폼을 탐구하며, Databricks Notebooks를 활용한 피처 엔지니어링과 MLflow를 통한 모델 라이프사이클 추적 등의 주제를 다룹니다. 또한 Mosaic AI Model Serving을 통한 실시간 모델 추론에 대해 배우고, AutoML을 통해 Databricks의 모델 개발에 대한 “투명한 접근 방식(glass box approach)”을 경험하게 됩니다. 본 과정에는 강사가 진행하는 세 가지 데모가 포함되어 있으며, 데모에서 다룬 개념을 강화하는 종합 실습으로 마무리됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28055","entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-databricks-asset-bundles-korean-3940"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-databricks-asset-bundles-korean-3940"}}],"nid":28055,"vid":217360,"title":"Automated Deployment with Databricks Asset Bundles - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 DevOps 원칙과 이를 Databricks 프로젝트에 적용하는 방법을 포괄적으로 검토합니다. 핵심 DevOps, DataOps, 지continuous integration (CI), continuous deployment (CD), 테스트에 대한 개요로 시작하여 이러한 원칙을 데이터 엔지니어링 파이프라인에 적용하는 방법을 탐구합니다.
이어서 CI/CD 프로세스 내 지속적 배포에 초점을 맞추며, 프로젝트 배포를 위한 Databricks REST API, SDK, CLI와 같은 도구를 살펴봅니다. Databricks Asset Bundles(DAB)와 CI/CD 프로세스 내에서의 역할을 학습하게 됩니다. 주요 구성 요소, 폴더 구조, Databricks 내 다양한 대상 환경에 걸친 배포 간소화 방식을 심층적으로 다룹니다. 또한 Databricks CLI를 활용하여 서로 다른 구성의 다중 환경에 대해 변수 추가, 수정, 검증, 배포 및 실행하는 방법을 익히게 됩니다.
마지막으로, Visual Studio Code를 인터랙티브 개발 환경(IDE)으로 활용하여 로컬에서 Databricks Asset Bundles를 빌드, 테스트, 배포하는 방법을 소개함으로써 개발 프로세스를 최적화합니다. GitHub Actions를 활용한 배포 파이프라인 자동화를 통해 Databricks Asset Bundles의 CI/CD 워크플로우를 강화하는 방법에 대한 소개로 강좌를 마무리합니다.
본 과정 수료 시, Databricks Asset Bundles를 활용한 Databricks 프로젝트 배포 자동화 역량을 갖추게 되어 DevOps 관행을 통해 효율성을 향상시킬 수 있습니다.
참고: 이 강좌는 ‘Databricks을 사용한 고급 데이터 엔지니어링’ 시리즈의 네 번째 강좌입니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28142","entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4344"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4344"}}],"nid":28142,"vid":217447,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 Databricks 플랫폼의 핵심 구성 요소와 Delta Lake를 활용한 Apache Spark를 다루며, 레이크하우스 아키텍처, Unity Catalog, ACID 트랜잭션 및 테이블 유지 관리와 같은 데이터 관리 기법에 중점을 둡니다. 또한 파티셔닝, 셔플, 튜닝 도구를 통해 쿼리 성능을 최적화하는 방법을 학습하고, Spark UI를 활용하여 애플리케이션을 모니터링하고 병목 현상을 해결하는 방법을 교육합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-17T14:00:00"},"endDate":{"value":"2026-12-17T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28216","entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4848"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4848"}}],"nid":28216,"vid":217521,"title":"Get Started with Data Governance on Databricks - Korean","price":"0.00","duration":10800,"body":{"processed":"이 강의에서는 Unity Catalog와 Databricks의 세밀한 접근 통제를 실습 데모와 캡스톤 랩을 통해 탐구하게 됩니다. 테이블 유형, 카탈로그 및 스키마 구성, 그룹 기반 접근 관리, 접근 제어 마이그레이션 전략에 대해 배우게 됩니다. 이 과정에는 행 수준 보안 및 컬럼 마스킹을 사용한 세분화된 접근 제어 적용, 속성 기반 접근 제어, 제어 결합, 제어 마이그레이션, 그리고 포괄적인 거버넌스 구현을 위한 실습 데모가 포함되어 있습니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28324","entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-3081"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-3081"}}],"nid":28324,"vid":217629,"title":"Databricks Performance Optimization - Korean","price":"0.00","duration":14400,"body":{"processed":"이 과정에서는 Spark와 Delta Lake를 활용해 워크로드와 물리적 레이아웃을 최적화하는 방법을 배우고, Spark UI를 분석하여 성능을 평가하고 애플리케이션을 디버깅하는 방법을 익히게 됩니다. 스트리밍, 유동적 클러스터링, 데이터 스키핑, 캐싱, 포토네이션 등 다양한 주제를 다룰 예정입니다.
메모: 이 과정은 'Databrick을 사용한 고급 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28394","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3573"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-machine-learning-korean-3573"}}],"nid":28394,"vid":217699,"title":"Get Started with Databricks for Machine Learning - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform을 활용하여 기본 머신러닝 워크플로를 실행하고 데이터 사이언스 워크로드를 지원하는 데 필요한 기초 기술을 습득하게 됩니다. 머신러닝 실무자의 관점에서 플랫폼을 탐구하며, Databricks Notebooks를 활용한 피처 엔지니어링과 MLflow를 통한 모델 라이프사이클 추적 등의 주제를 다룹니다. 또한 Mosaic AI Model Serving을 통한 실시간 모델 추론에 대해 배우고, AutoML을 통해 Databricks의 모델 개발에 대한 “투명한 접근 방식(glass box approach)”을 경험하게 됩니다. 본 과정에는 강사가 진행하는 세 가지 데모가 포함되어 있으며, 데모에서 다룬 개념을 강화하는 종합 실습으로 마무리됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28058","entityUrl":{"path":"/kr/training/catalog/databricks-data-privacy-korean-3948"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-data-privacy-korean-3948"}}],"nid":28058,"vid":217363,"title":"Databricks Data Privacy - Korean","price":"750.00","duration":14400,"body":{"processed":"이 콘텐츠는 Databricks 내에서 데이터 프라이버시를 관리하는 포괄적인 가이드를 제공합니다. 델타 레이크 아키텍처, 지역별 데이터 격리, GDPR/CCPA 준수, 변경 데이터 피드(CDF) 사용법 등 핵심 주제를 다룹니다. 실습 데모와 핸즈온 랩을 통해 참가자는 민감한 데이터를 보호하고 규정 준수를 보장하기 위한 Unity catalog 기능을 활용하는 방법을 배우며, 데이터 무결성을 효과적으로 보호할 수 있는 역량을 강화합니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-19T14:00:00"},"endDate":{"value":"2026-11-19T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28143","entityUrl":{"path":"/kr/training/catalog/apache-spark-programming-with-databricks-korean-4347"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/apache-spark-programming-with-databricks-korean-4347"}}],"nid":28143,"vid":217448,"title":"Apache Spark Programming with Databricks - Korean","price":"1500.00","duration":57600,"body":{"processed":"이 과정은 Databricks를 사용하여 Apache Spark 프로그래밍을 배우기 위한 적절한 시작점 역할을 합니다.
아래에서는 이 과정에 포함된 4개의 4시간짜리 모듈을 각각 설명합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Introduction to Apache Spark
이 입문자 친화적인 과정에서는 대규모 데이터 처리를 위한 Apache Spark의 기본 개념을 다룹니다. Spark의 분산 아키텍처를 탐험하고, DataFrame API를 숙달하며, Python을 사용하여 데이터를 읽고, 쓰고, 처리하는 방법을 학습합니다. 실습 예제를 통해 Spark 변환 및 액션을 효율적으로 실행하는 데 필요한 기술을 습득합니다.
Developing Applications with Apache Spark
Apache Spark를 활용한 확장 가능한 데이터 처리를 이 과정에서 마스터하십시오. 효율적인 ETL 파이프라인을 구축하고, 고급 분석을 수행하며, Spark의 DataFrame API를 사용하여 분산 데이터 변환을 최적화하는 방법을 학습합니다. 그룹화, 집계, 조인, 집합 운영 및 윈도우 함수를 탐험합니다. 배열, 맵, 구조체와 같은 복잡한 데이터 유형을 다루면서 성능 최적화를 위한 모범 사례를 적용합니다.
Stream Processing and Analysis with Apache Spark
이 과정은 Databricks에서 Spark Structured Streaming API를 사용하여 확장 가능하고 내결함성을 갖춘 스트림 처리 애플리케이션을 개발하는 방법을 학습자에게 안내합니다.
Monitoring and Optimizing Apache Spark Workloads on Databricks
이 과정은 Databricks 플랫폼의 핵심 구성 요소와 Delta Lake를 활용한 Apache Spark를 다루며, 레이크하우스 아키텍처, Unity Catalog, ACID 트랜잭션 및 테이블 유지 관리와 같은 데이터 관리 기법에 중점을 둡니다. 또한 파티셔닝, 셔플, 튜닝 도구를 통해 쿼리 성능을 최적화하는 방법을 학습하고, Spark UI를 활용하여 애플리케이션을 모니터링하고 병목 현상을 해결하는 방법을 교육합니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28217","entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4849"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-data-governance-on-databricks-korean-4849"}}],"nid":28217,"vid":217522,"title":"Get Started with Data Governance on Databricks - Korean","price":"75.00","duration":10800,"body":{"processed":"이 강의에서는 Unity Catalog와 Databricks의 세밀한 접근 통제를 실습 데모와 캡스톤 랩을 통해 탐구하게 됩니다. 테이블 유형, 카탈로그 및 스키마 구성, 그룹 기반 접근 관리, 접근 제어 마이그레이션 전략에 대해 배우게 됩니다. 이 과정에는 행 수준 보안 및 컬럼 마스킹을 사용한 세분화된 접근 제어 적용, 속성 기반 접근 제어, 제어 결합, 제어 마이그레이션, 그리고 포괄적인 거버넌스 구현을 위한 실습 데모가 포함되어 있습니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28327","entityUrl":{"path":"/kr/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-korean-3084"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-korean-3084"}}],"nid":28327,"vid":217632,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Korean","price":"0.00","duration":14400,"body":{"processed":"이 과정은 Spark Structured Streaming과 Delta Lake에 대한 포괄적인 이해를 제공하며, 여기에는 계산 모델, 스트리밍 읽기 구성, 스트리밍 환경에서의 데이터 품질 유지 관리 등이 포함됩니다.
참고: 이 과정은 'Databricks을 사용한 고급 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28406","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3667"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-generative-ai-korean-3667"}}],"nid":28406,"vid":217711,"title":"Get Started with Databricks for Generative AI - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks Data Intelligence Platform에 대한 실용적인 입문 과정으로, 생성형 AI 시스템을 구축하고 배포하기 위한 핵심 구성 요소와 기능에 중점을 둡니다. 참가자들은 Databricks가 확장 가능한 생성형 AI 솔루션 개발을 어떻게 지원하는지 학습하고, AI Search, Agent Framework, 그리고 모델 추적 및 로깅을 위한 MLflow의 생성형 AI 기능과 같은 도구들을 탐험합니다. 이 과정에는 Retrieval-Augmented Generation (RAG) 파이프라인의 구축 및 평가, 생성형 AI 에이전트 배포, 그리고 성능 최적화를 위한 평가 프레임워크 활용에 관한 실습 경험이 포함됩니다. 과정을 마치면 학습자들은 Databricks Data Intelligence Platform에서 일반적인 생성형 AI 애플리케이션을 설계, 배포 및 모니터링할 수 있는 역량을 갖추게 됩니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-15T14:00:00"},"endDate":{"value":"2026-12-15T16:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2027-01-20T14:00:00"},"endDate":{"value":"2027-01-20T16:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28072","entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4009"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/aibi-for-data-analysts-korean-4009"}}],"nid":28072,"vid":217377,"title":"AI/BI for Data Analysts - Korean","price":"750.00","duration":14400,"body":{"processed":"이 코스에서는 데이터 분석가가 Databricks에서 AI/BI Dashboards를 설계, 구축, 게시 및 운영하는 방법을 배웁니다. AI/BI Dashboards는 거버넌스가 적용된 Unity Catalog 데이터를 대화형 시각화, 필터, Genie 통합과 결합하여, 비즈니스 사용자가 코드를 작성하지 않고도 답을 탐색할 수 있게 합니다.
이 코스는 하나의 엔드 투 엔드 구축을 따라 진행됩니다. Unity Catalog의 소스 테이블에서 시작하여, 게시되고 모니터링되는 여러 페이지 대시보드로 마무리합니다. 그 과정에서 대시보드가 더 넓은 Databricks AI/BI 제품군에서 어떻게 자리매김하는지, 그리고 Genie, 데이터 세트, 시각화, 필터가 각각 워크플로의 어디에 들어맞는지 배웁니다.
다루는 내용은 다음과 같습니다.
• AI/BI Dashboards의 기초와, 그것이 Genie 및 Databricks 플랫폼의 나머지 요소와 어떻게 관련되는지.
• Unity Catalog에서 소스 데이터를 탐색하고 SQL로 재사용 가능한 대시보드 데이터 세트를 설계하기.
• 시각화(KPI, 추세, 세부 분석) 작성 및 깔끔한 여러 페이지 대시보드 구성.
• Genie Code를 사용하여 자연어 프롬프트로부터 SQL, 차트, 필터의 초안을 작성하기.
• 필터를 추가하여 대시보드를 대화형으로 만들고 보는 사람의 질문에 응답하도록 하기.
• 적절한 사람이 대시보드를 보고 편집할 수 있도록 게시, 공유, 권한 관리하기.
• 예약된 새로 고침, 캐싱, 사용량 모니터링과 함께 대시보드를 프로덕션에서 운영하기.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-16T09:00:00"},"endDate":{"value":"2026-10-16T13:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-12-03T09:00:00"},"endDate":{"value":"2026-12-03T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28149","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-platform-administration-korean-4471"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-platform-administration-korean-4471"}}],"nid":28149,"vid":217454,"title":"Get Started with Databricks Platform Administration - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform의 플랫폼 관리 기초를 학습합니다. Databricks 환경 내에서 효과적인 데이터 거버넌스를 위한 핵심 구성 요소인 Unity Catalog에 대한 포괄적인 개요를 제공합니다. 총 5개의 모듈로 구성되며, Databricks 인프라와 데이터 인텔리전스 플랫폼에 대한 상세한 소개로 시작하여 Databricks Workspace에 대한 심층적인 안내를 포함합니다. Unity Catalog 내의 데이터 거버넌스 원칙을 탐구하며, 주요 개념, 아키텍처 및 역할을 다룹니다. 또한 클러스터 및 SQL 웨어하우스를 포함한 Unity Catalog 메타스토어 및 compute 리소스 관리를 중점적으로 다룹니다. 마지막으로, 권한, 세분화된 액세스 제어, 데이터 객체 거버넌스 방법을 학습하여 데이터 액세스 제어를 완전히 습득하게 됩니다. 과정을 마치면 Unity Catalog를 관리하여 효과적인 데이터 거버넌스를 구현하고, compute 리소스를 최적화하며, 강력한 데이터 보안 전략을 시행하는 데 필요한 핵심 역량을 갖추게 됩니다. Databricks Labs 구독 구매 시, 실제 Databricks Workspace 환경에서 학습한 내용을 실습할 수 있는 종합 실습 과제로 과정이 마무리됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28250","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-2496"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-engineering-korean-2496"}}],"nid":28250,"vid":217555,"title":"Get Started with Databricks for Data Engineering - Korean","price":"0.00","duration":7200,"body":{"processed":"이 코스에서는 Databricks Data Intelligence Platform에서 기본적인 데이터 엔지니어링 워크플로를 수행하는 데 필요한 기초 기술을 소개합니다. 워크스페이스를 살펴보고, Unity Catalog를 사용하며, 데이터 엔지니어가 Databricks에서 일상적으로 활용하는 핵심 구성 요소를 학습합니다.
이 코스는 실습 중심으로 진행됩니다. 먼저 워크스페이스에 익숙해진 다음, 각 주제별로 데모와 랩 노트북을 짝지어 진행합니다. 데모에서는 강사 또는 가이드 노트북과 함께 개념을 살펴보고, 랩에서는 방금 학습한 내용을 직접 적용합니다.
다루는 내용은 다음과 같습니다.
• Databricks Data Intelligence Platform의 개요와 Databricks Workspace, Unity Catalog, 노트북이 어떻게 함께 작동하는지.
• Delta Lake 테이블의 생성 및 관리.
• INSERT, UPDATE, DELETE를 사용한 데이터 변경.
• Delta 테이블의 버전 기록 및 타임 트래블 살펴보기.
• Lakeflow Connect 옵션(CTAS, 업로드 UI, COPY INTO)을 사용한 데이터 수집.
• 브론즈, 실버, 골드 계층을 통해 데이터를 변환하는 메달리온 아키텍처 파이프라인 구축.
• Lakeflow Jobs를 사용한 파이프라인 자동화.
• (보너스) Spark Declarative Pipelines를 사용한 선언형 파이프라인 구축.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28328","entityUrl":{"path":"/kr/training/catalog/machine-learning-operations-korean-3107"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/machine-learning-operations-korean-3107"}}],"nid":28328,"vid":217633,"title":"Machine Learning Operations - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 참가자들이 MLOps와 모델 라이프사이클 관리에 중점을 두어 머신 러닝 모델 운영을 종합적으로 탐구할 수 있도록 가이드를 제공합니다. 초반부에서는 필수 MLOps 구성 요소와 모범 사례를 다루며, 참가자들이 머신 러닝 모델을 효과적으로 운영화하기 위한 탄탄한 기반을 갖출 수 있도록 합니다. 과정 후반부에서는 모델 라이프사이클의 기본 개념을 심층적으로 살펴보고, Unity Catalog와 연계된 Model Registry를 활용하여 효율적인 모델 관리를 위해 라이프사이클을 원활하게 탐색하는 방법을 시연합니다. 과정이 마무리될 즈음에는 참가자들이 실질적인 인사이트와 MLOps 원칙에 대한 균형 잡힌 이해를 갖추게 되며, 복잡한 머신 러닝 모델 운영 환경을 탐색하는 데 필요한 역량을 습득하게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28430","entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3839"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3839"}}],"nid":28430,"vid":217735,"title":"DevOps Essentials for Data Engineering - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 Databricks를 사용하는 데이터 엔지니어를 위해 특별히 설계된 소프트웨어 엔지니어링 모범 사례와 DevOps 원칙을 탐구합니다. 참가자는 코드 품질, 버전 관리, 문서화, 테스트 등 핵심 주제에 대한 탄탄한 기초를 쌓게 됩니다. 이 과정은 DevOps를 중점적으로 다루며, 핵심 구성 요소, 이점, 그리고 데이터 엔지니어링 워크플로우 최적화에 있어 지속적 통합 및 제공(CI/CD)의 역할을 다룹니다.
PySpark에서 모듈성 원칙을 적용하여 재사용 가능한 컴포넌트를 만들고 코드를 효율적으로 구조화하는 방법을 학습합니다. 실습 경험에는 pytest 프레임워크를 사용하여 PySpark 함수에 대한 단위 테스트를 설계하고 구현하는 것이 포함되며, 이후 신뢰성 확보를 위해 Spark Declarative Pipeline과 Jobs를 활용한 Databricks 데이터 파이프라인의 통합 테스트로 이어집니다.
또한 이 과정에서는 지속적 통합 방식을 통합하기 위해 Databricks Git Folders를 사용하는 것을 포함하여 Databricks 내의 필수 Git 운영을 다룹니다. 마지막으로, REST API, CLI, SDK, Declarative Automation Bundles(DABs)와 같은 Databricks 자산의 다양한 배포 방법을 개괄적으로 살펴봄으로써 파이프라인을 배포하고 관리하는 기술에 대한 지식을 제공합니다.
과정을 마치면 소프트웨어 엔지니어링 및 DevOps 모범 사례에 능숙해져, 확장 가능하고 유지 관리가 용이하며 효율적인 데이터 엔지니어링 솔루션을 구축할 수 있게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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참고: 이 강좌는 '데이터브릭을 사용한 고급 데이터 엔지니어링' 시리즈의 두 번째 강좌입니다.
Languages Available: Languages Available: English | 日本語 | Português BR | 한국어
이 과정은 분산 아키텍처와 대규모 데이터 처리를 위한 실제 응용 프로그램에 중점을 두고 Apache Spark™에 대한 필수 지식을 제공합니다. 참가자는 프로그래밍 프레임워크를 탐색하고 Spark DataFrame API를 배우며 Python 기반 Spark 워크플로를 사용하여 데이터를 읽고, 쓰고, 변환하는 기술을 개발하십시오.
Languages Available: English | 한국어
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아래에서는 이 과정에 포함된 4개의 4시간짜리 모듈에 대해 각각 설명합니다.
참고: Databricks Academy는 Databricks 환경 내 강의 세션을 노트북 기반 형식으로 전환하며, 첫 모듈 강의에서 슬라이드 데크 사용을 중단합니다. 강의 노트북은 Vocareum 랩 환경에서 확인할 수 있습니다.
Advanced Techniques with Apache Spark Declarative Pipelines
이 과정에서는 생산 수준의 스트리밍 파이프라인을 구축하기 위한 Databricks의 Apache Spark Declarative Pipelines(SDP)를 살펴봅니다. 실제 레이크하우스 엔지니어링에 필수적인 고급 설계 패턴, 강력한 데이터 품질 적용, 그리고 크로스 플랫폼 통합에 대해 학습합니다.
과정 전반에 걸쳐 현대적인 데이터 수집 및 처리 기법을 심층적으로 다루며, 레이아웃 최적화를 위한 Liquid 클러스터링과 혼합 스키마 이벤트를 위한 멀티플렉스 스트리밍 패턴 등의 도구를 숙달합니다. 모듈을 마치면 스키마 진화를 자신 있게 처리하고, 변경 데이터 캡처(CDC)를 자동화하며, 데이터 무결성을 보장하는 방법을 습득하게 됩니다.
강의와 실습 데모를 통해 다음을 수행합니다:
• 다중 소스 데이터를 단일 브론즈 테이블로 수집하는 멀티 플로우 파이프라인을 구축합니다.
• 실버 및 골드 레이어 전반에 걸쳐 Liquid 클러스터링과 데이터 품질 Expectations를 적용합니다.
• 크로스 플랫폼 데이터 접근을 위해 Iceberg UniForm과 함께 멀티플렉스 패턴을 구현합니다.
• AUTO CDC INTO를 사용하여 SCD Type 2 이력 추적을 자동화합니다.
• 잘못된 레코드를 감사하고 관리하기 위한 데이터 무손실 격리 파이프라인을 설계합니다.
Databricks Data Privacy
이 콘텐츠는 Databricks 내에서 데이터 프라이버시를 관리하는 포괄적인 가이드를 제공합니다. 델타 레이크 아키텍처, 지역별 데이터 격리, GDPR/CCPA 준수, 변경 데이터 피드(CDF) 사용법 등 핵심 주제를 다룹니다. 실습 데모와 핸즈온 랩을 통해 참가자는 민감한 데이터를 보호하고 규정 준수를 보장하기 위한 Unity catalog 기능을 활용하는 방법을 배우며, 데이터 무결성을 효과적으로 보호할 수 있는 역량을 강화합니다.
Databricks Performance Optimization
이 과정에서는 Spark와 Delta Lake를 활용해 워크로드와 물리적 레이아웃을 최적화하는 방법을 배우고, Spark UI를 분석하여 성능을 평가하고 애플리케이션을 디버깅하는 방법을 익히게 됩니다. 스트리밍, 유동적 클러스터링, 데이터 스키핑, 캐싱, 포토네이션 등 다양한 주제를 다룰 예정입니다.
Automated Deployment with Declarative Automation Bundles
이 과정은 DevOps 원칙과 Databricks 프로젝트에 대한 적용을 종합적으로 다룹니다. 핵심 DevOps, DataOps, 지속적 통합(CI), 지속적 배포(CD) 및 테스트에 대한 개요로 시작하며, 이러한 원칙을 데이터 엔지니어링 파이프라인에 적용하는 방법을 살펴봅니다.
이어서 CI/CD 프로세스 내의 지속적 배포에 초점을 맞추어, 프로젝트 배포를 위한 Databricks REST API, SDK, CLI와 같은 도구를 살펴봅니다. Declarative Automation Bundles(DABs)와 이것이 CI/CD 프로세스에서 어떤 역할을 하는지 학습합니다. 주요 구성 요소, 폴더 구조, 그리고 Databricks의 다양한 대상 환경에 걸쳐 배포를 간소화하는 방법을 심층적으로 살펴봅니다. 또한 Databricks CLI를 사용하여 서로 다른 구성을 가진 여러 환경에 대해 Declarative Automation Bundles에 변수를 추가하고, 수정, 검증, 배포 및 실행하는 방법도 학습합니다.
마지막으로, 이 과정에서는 Declarative Automation Bundles를 로컬에서 빌드, 테스트 및 배포하기 위한 대화형 개발 환경(IDE)으로 Visual Studio Code를 소개하며, 개발 프로세스를 최적화합니다. 과정의 마무리로 GitHub Actions를 사용하여 배포 파이프라인을 자동화함으로써 Declarative Automation Bundles를 활용한 CI/CD 워크플로를 강화하는 방법을 소개합니다.
이 과정을 마치면 DevOps 방식을 통해 효율성을 높이면서 Declarative Automation Bundles를 활용하여 Databricks 프로젝트 배포를 자동화할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
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이 과정은 Databricks 환경에서 머신러닝 워크플로를 완벽하게 마스터하기 위한 여러분의 입문서가 되어 줄 것입니다. 전문 강사진의 지도 아래 데이터 준비, 모델 개발, 배포 및 운영에 이르는 전 과정을 깊이 있게 탐구해 보세요. Databricks에 최적화된 데이터 탐색, 모델 훈련, 그리고 배포 전략에 필요한 핵심 기술을 습득하게 됩니다. 과정을 마치면 Databricks platform 내에서 전체 머신러닝 수명 주기를 주도적으로 관리할 수 있는 지식과 자신감을 갖추게 되며, 이를 바탕으로 견고한 머신러닝 솔루션을 효율적으로 구축하고 배포할 수 있게 될 것입니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
머신러닝을 위한 데이터 준비
이 과정은 Databricks를 사용하여 머신 러닝을 위한 데이터 준비의 기본 사항에 중점을 둡니다. 참가자들은 전통적인 머신 러닝 애플리케이션에 맞게 데이터를 탐색, 정제 및 구성하는 데 필요한 핵심 기술을 학습합니다. 주요 주제로는 데이터 시각화, 특성 엔지니어링, 최적의 특성 저장 전략이 포함됩니다. 실습 과제를 통해 참가자들은 Databricks 내에서 머신 러닝을 위한 데이터 세트를 효율적으로 준비하는 실무 경험을 쌓게 됩니다. 이 과정은 어소시에이트 수준의 데이터 과학자 및 머신 러닝 실무자, 그리고 데이터 준비 역량을 강화하고자 하는 개인을 대상으로 설계되었으며, 성공적인 머신 러닝 모델 배포를 위한 탄탄한 기반을 제공합니다.
머신러닝 모델 개발
이 종합 과정은 Databricks에서 전통적인 머신 러닝 모델을 개발하기 위한 실용적인 가이드를 제공하며, 인기 있는 ML 라이브러리를 사용한 실습 데모 및 Workflows에 중점을 둡니다. 참가자들은 회귀 및 클러스터링을 포함한 핵심 ML 기법을 탐험하면서 Databricks의 강력한 기능을 활용하게 됩니다. 이 과정은 모델 추적을 위한 MLflow 통합, 특성 관리를 위한 Databricks Feature Store, 그리고 하이퍼파라미터 튜닝을 위한 Optuna를 다룹니다. 또한 참가자들은 자연어, MCP 연결, 지침 및 스킬을 활용하여 전체 ML 라이프사이클을 가이드하는 Databricks의 AI 기반 코딩 어시스턴트인 Genie Code를 통해 모델 개발을 가속화하는 방법을 학습합니다. 과정이 끝나면 학습자들은 Databricks 환경에서 머신 러닝 모델을 효율적으로 개발, 최적화 및 배포할 수 있는 실무 역량을 갖추게 됩니다.
머신러닝 모델 배포
이 과정은 세 가지 주요 머신러닝 배포 전략을 소개하고, Databricks 환경에서 각 전략을 실제로 구현하는 방법을 보여주기 위해 설계되었습니다. 모델 배포의 기초 원리를 탐구한 후, 과정은 배치 추론(Batch Inference) 분야로 심층적으로 들어갑니다. 배치 추론 시나리오에서 모델을 활용하는 방법에 대한 실습 시연과 랩(Lab) 실습을 제공하며, 성능 최적화를 위한 고려 사항들도 함께 다룹니다. 과정의 두 번째 파트에서는 파이프라인 배포(Pipeline Deployment)에 대해 포괄적으로 다루며, 마지막 파트에서는 실시간 배포(Real-time Deployment)에 집중하여 학습을 진행합니다. 참가자들은 실습 시연 및 랩 세션에 참여하여, Model Serving을 활용해 모델을 배포하고 해당 서빙 엔드포인트를 이용해 실시간 추론을 수행하게 됩니다.
머신러닝 운영
본 과정은 MLOps 및 모델 수명 주기 관리에 중점을 두고, 머신러닝 모델 운영 전반을 심층적으로 탐구할 수 있도록 참가자들을 안내합니다. 과정의 초반부에서는 필수적인 MLOps 구성 요소와 모범 사례를 다루며, 참가자들이 머신러닝 모델을 효과적으로 운영 환경에 적용하는 데 필요한 탄탄한 기초를 다질 수 있도록 지원합니다. 후반부에서는 모델 수명 주기의 기본 원리를 상세히 살펴보고, Unity Catalog와 연계된 Model Registry를 활용하여 모델 수명 주기를 원활하게 관리하는 방법을 시연합니다. 과정을 마치게 되면, 참가자들은 MLOps 원리에 대한 실질적인 통찰력과 포괄적인 이해를 갖추게 되며, 복잡다단한 머신러닝 모델 운영 환경을 능숙하게 다룰 수 있는 역량을 확보하게 될 것입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28432","entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3877"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3877"}}],"nid":28432,"vid":217737,"title":"DevOps Essentials for Data Engineering - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks를 사용하여 작업하는 데이터 엔지니어를 위해 특별히 설계된 소프트웨어 엔지니어링 모범 사례와 DevOps 원칙을 살펴봅니다. 참가자는 코드 품질, 버전 제어, 문서화, 테스트와 같은 핵심 주제에 대한 강력한 기반을 구축하게 됩니다. 이 과정에서는 DevOps를 강조하여 핵심 구성 요소, 이점, 데이터 엔지니어링 워크플로 최적화에서 지속적인 통합 및 배포(CI/CD)의 역할에 대해 다룹니다.
PySpark에서 모듈성 원칙을 적용하여 재사용 가능한 구성 요소를 만들고 효율적으로 코드를 구성하는 방법을 학습합니다. 실습 경험에는 pytest 프레임워크를 사용하여 PySpark 함수에 대한 단위 테스트를 설계하고 구현하는 것과 DLT 및 Workflows를 사용하여 Databricks 데이터 파이프라인에 대한 통합 테스트를 수행하여 안정성을 보장하는 것이 포함됩니다.
또한 이 과정에서는 Databricks Git 폴더를 사용하여 지속적인 통합 관행을 통합하는 것을 포함하여 Databricks 내에서 필수적인 Git 작업도 다룹니다. 마지막으로 REST API, CLI, SDK, Databricks Asset Bundles(DAB) 등 Databricks 자산에 대한 다양한 배포 방법을 간략하게 살펴보고 파이프라인을 배포하고 관리하는 기술에 대한 지식을 얻습니다.
과정을 마치면 소프트웨어 엔지니어링과 DevOps 모범 사례에 능숙해져서 확장 가능하고 유지 관리가 가능하며 효율적인 데이터 엔지니어링 솔루션을 구축할 수 있게 됩니다.
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28082","entityUrl":{"path":"/kr/training/catalog/databricks-data-privacy-korean-4033"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-data-privacy-korean-4033"}}],"nid":28082,"vid":217387,"title":"Databricks Data Privacy - Korean","price":"75.00","duration":10800,"body":{"processed":"이 콘텐츠는 Databricks 내에서 데이터 프라이버시를 관리하는 포괄적인 가이드를 제공합니다. 델타 레이크 아키텍처, 지역별 데이터 격리, GDPR/CCPA 준수, 변경 데이터 피드(CDF) 사용법 등 핵심 주제를 다룹니다. 실습 데모와 핸즈온 랩을 통해 참가자는 민감한 데이터를 보호하고 규정 준수를 보장하기 위한 Unity catalog 기능을 활용하는 방법을 배우며, 데이터 무결성을 효과적으로 보호할 수 있는 역량을 강화합니다.
참고: 이 강좌는 '데이터브릭을 사용한 고급 데이터 엔지니어링' 시리즈의 두 번째 강좌입니다.
Languages Available: Languages Available: English | 日本語 | Português BR | 한국어
이 과정은 분산 아키텍처와 대규모 데이터 처리를 위한 실제 응용 프로그램에 중점을 두고 Apache Spark™에 대한 필수 지식을 제공합니다. 참가자는 프로그래밍 프레임워크를 탐색하고 Spark DataFrame API를 배우며 Python 기반 Spark 워크플로를 사용하여 데이터를 읽고, 쓰고, 변환하는 기술을 개발하십시오.
Languages Available: English | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28276","entityUrl":{"path":"/kr/training/catalog/databricks-fundamentals-accreditation-korean-2765"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-fundamentals-accreditation-korean-2765"}}],"nid":28276,"vid":217581,"title":"Databricks Fundamentals Accreditation - Korean","price":"0.00","duration":1800,"body":{"processed":"Databricks 기초 인증에 오신 것을 환영합니다. 10문항으로 구성된 이 퀴즈를 통해 Databricks 데이터 인텔리전스 플랫폼에 대한 지식을 테스트합니다. 이 퀴즈를 성공적으로 완료하면 배지 공급업체인 Accredible을 통해 48시간 이내에 배지를 받게 됩니다. 행운을 빕니다!
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"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28334","entityUrl":{"path":"/kr/training/catalog/deploy-workloads-with-lakeflow-jobs-korean-3282"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/deploy-workloads-with-lakeflow-jobs-korean-3282"}}],"nid":28334,"vid":217639,"title":"Deploy Workloads with Lakeflow Jobs - Korean","price":"75.00","duration":14400,"body":{"processed":"Deploy Workloads with Lakeflow Jobs 과정에서는 Databricks 에코시스템 내에서 통합 오케스트레이션 플랫폼으로서 Lakeflow Jobs를 사용하여 데이터, 분석 및 AI 워크플로를 오케스트레이션하고 자동화하는 방법을 학습합니다.
• 방향성 비순환 그래프(DAG)를 사용하여 데이터 워크로드를 설계 및 구현하고, 다양한 스케줄링 옵션을 구성하며, 조건부 태스크 실행, 실행 조건 의존성, for each 루프와 같은 고급 워크플로 기능을 구현하는 방법을 학습합니다.
• 본 과정에서는 적절한 compute 선택, 모듈식 오케스트레이션, 오류 처리 기법, 내결함성 설계를 통해 견고하고 생산 준비가 완료된 파이프라인을 생성하기 위한 모범 사례를 다루며, 이 모든 것이 Databricks Data Intelligence Platform 내에 기본적으로 통합되어 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28433","entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3878"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/devops-essentials-for-data-engineering-korean-3878"}}],"nid":28433,"vid":217738,"title":"DevOps Essentials for Data Engineering - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks를 사용하여 작업하는 데이터 엔지니어를 위해 특별히 설계된 소프트웨어 엔지니어링 모범 사례와 DevOps 원칙을 살펴봅니다. 참가자는 코드 품질, 버전 제어, 문서화, 테스트와 같은 핵심 주제에 대한 강력한 기반을 구축하게 됩니다. 이 과정에서는 DevOps를 강조하여 핵심 구성 요소, 이점, 데이터 엔지니어링 워크플로 최적화에서 지속적인 통합 및 배포(CI/CD)의 역할에 대해 다룹니다.
PySpark에서 모듈성 원칙을 적용하여 재사용 가능한 구성 요소를 만들고 효율적으로 코드를 구성하는 방법을 학습합니다. 실습 경험에는 pytest 프레임워크를 사용하여 PySpark 함수에 대한 단위 테스트를 설계하고 구현하는 것과 DLT 및 Workflows를 사용하여 Databricks 데이터 파이프라인에 대한 통합 테스트를 수행하여 안정성을 보장하는 것이 포함됩니다.
또한 이 과정에서는 Databricks Git 폴더를 사용하여 지속적인 통합 관행을 통합하는 것을 포함하여 Databricks 내에서 필수적인 Git 작업도 다룹니다. 마지막으로 REST API, CLI, SDK, Databricks Asset Bundles(DAB) 등 Databricks 자산에 대한 다양한 배포 방법을 간략하게 살펴보고 파이프라인을 배포하고 관리하는 기술에 대한 지식을 얻습니다.
과정을 마치면 소프트웨어 엔지니어링과 DevOps 모범 사례에 능숙해져서 확장 가능하고 유지 관리가 가능하며 효율적인 데이터 엔지니어링 솔루션을 구축할 수 있게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28083","entityUrl":{"path":"/kr/training/catalog/sql-analytics-on-databricks-korean-4035"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/sql-analytics-on-databricks-korean-4035"}}],"nid":28083,"vid":217388,"title":"SQL Analytics on Databricks - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks SQL에 특히 초점을 맞춰 Databricks를 사용하여 데이터 분석을 효과적으로 수행하는 방법을 학습합니다. Databricks 데이터 애널리스트로서 귀하의 책임에는 관련 데이터를 찾고, 잠재적인 응용 프로그램을 위해 데이터를 분석하고, 귀중한 비즈니스 통찰력을 제공하는 형식으로 데이터를 변환하는 것이 포함됩니다.
또한 Databricks Data Intelligence Platform에서 Notebooks, SQL Editor, Databricks SQL과 같은 도구를 사용하여 데이터 객체를 관리하는 역할과 이를 조작하는 방법을 이해하게 됩니다.
또한, 데이터 자산과 전반적인 플랫폼을 관리하는 데 있어 Unity Catalog의 중요성에 대해서도 알아봅니다. 마지막으로, 이 과정에서는 Databricks가 어떻게 성능 최적화를 용이하게 하는지에 대한 개요를 제공하고, Databricks에서 SQL 분석을 실행할 때 내부적으로 발생하는 프로세스를 이해하기 위해 Query Insights에 액세스하는 방법을 알려드립니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-22T13:00:00"},"endDate":{"value":"2026-10-22T17:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-12-04T09:00:00"},"endDate":{"value":"2026-12-04T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28165","entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4560"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4560"}}],"nid":28165,"vid":217470,"title":"Developing Applications with Apache Spark™ - Korean","price":"0.00","duration":7200,"body":{"processed":"이 실습 과정에서 Apache Spark로 확장 가능한 데이터 처리를 마스터하세요. Spark의 DataFrame API를 사용하여 효율적인 ETL 파이프라인을 구축하고, 고급 분석을 수행하며, 분산 데이터 변환을 최적화하는 방법을 알아보세요. 그룹화, 집계, 조인, 집합 연산 및 창 함수를 살펴봅니다. 배열, 맵, 구조체와 같은 복잡한 데이터 유형으로 작업하면서 성능 최적화를 위한 모범 사례를 적용하세요.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28278","entityUrl":{"path":"/kr/training/catalog/generative-ai-fundamentals-accreditation-korean-2784"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/generative-ai-fundamentals-accreditation-korean-2784"}}],"nid":28278,"vid":217583,"title":"Generative AI Fundamentals Accreditation - Korean","price":"0.00","duration":900,"body":{"processed":"Databricks 제너레이티브 AI 기초 - 인증에 오신 것을 환영합니다.
20분 동안 진행되는 이 평가는 제너레이티브 AI와 관련된 기본 개념에 대한 지식을 테스트하는 시험입니다.
이 평가를 성공적으로 완료하면 Databricks 제너레이티브 AI 기초 배지를 받게 됩니다.
학습 경로
수료 증명
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"28335","entityUrl":{"path":"/kr/training/catalog/deploy-workloads-with-lakeflow-jobs-korean-3283"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/deploy-workloads-with-lakeflow-jobs-korean-3283"}}],"nid":28335,"vid":217640,"title":"Deploy Workloads with Lakeflow Jobs - Korean","price":"0.00","duration":14400,"body":{"processed":"Deploy Workloads with Lakeflow Jobs 과정에서는 Databricks 에코시스템 내에서 통합 오케스트레이션 플랫폼으로서 Lakeflow Jobs를 사용하여 데이터, 분석 및 AI 워크플로를 오케스트레이션하고 자동화하는 방법을 학습합니다.
• 방향성 비순환 그래프(DAG)를 사용하여 데이터 워크로드를 설계 및 구현하고, 다양한 스케줄링 옵션을 구성하며, 조건부 태스크 실행, 실행 조건 의존성, for each 루프와 같은 고급 워크플로 기능을 구현하는 방법을 학습합니다.
• 본 과정에서는 적절한 compute 선택, 모듈식 오케스트레이션, 오류 처리 기법, 내결함성 설계를 통해 견고하고 생산 준비가 완료된 파이프라인을 생성하기 위한 모범 사례를 다루며, 이 모든 것이 Databricks Data Intelligence Platform 내에 기본적으로 통합되어 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28439","entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-declarative-automation-bundles-korean-3911"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/automated-deployment-with-declarative-automation-bundles-korean-3911"}}],"nid":28439,"vid":217744,"title":"Automated Deployment with Declarative Automation Bundles - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 DevOps 원칙과 Databricks 프로젝트에 대한 적용을 종합적으로 다룹니다. 핵심 DevOps, DataOps, 지속적 통합(CI), 지속적 배포(CD) 및 테스트에 대한 개요로 시작하며, 이러한 원칙을 데이터 엔지니어링 파이프라인에 적용하는 방법을 살펴봅니다.
이어서 CI/CD 프로세스 내의 지속적 배포에 초점을 맞추어, 프로젝트 배포를 위한 Databricks REST API, SDK, CLI와 같은 도구를 살펴봅니다. Declarative Automation Bundles(DABs)와 이것이 CI/CD 프로세스에서 어떤 역할을 하는지 학습합니다. 주요 구성 요소, 폴더 구조, 그리고 Databricks의 다양한 대상 환경에 걸쳐 배포를 간소화하는 방법을 심층적으로 살펴봅니다. 또한 Databricks CLI를 사용하여 서로 다른 구성을 가진 여러 환경에 대해 Declarative Automation Bundles에 변수를 추가하고, 수정, 검증, 배포 및 실행하는 방법도 학습합니다.
마지막으로, 이 과정에서는 Declarative Automation Bundles를 로컬에서 빌드, 테스트 및 배포하기 위한 대화형 개발 환경(IDE)으로 Visual Studio Code를 소개하며, 개발 프로세스를 최적화합니다. 과정의 마무리로 GitHub Actions를 사용하여 배포 파이프라인을 자동화함으로써 Declarative Automation Bundles를 활용한 CI/CD 워크플로를 강화하는 방법을 소개합니다.
이 과정을 마치면 DevOps 방식을 통해 효율성을 높이면서 Declarative Automation Bundles를 활용하여 Databricks 프로젝트 배포를 자동화할 수 있는 역량을 갖추게 됩니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-26T14:00:00"},"endDate":{"value":"2026-11-26T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28095","entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4099"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4099"}}],"nid":28095,"vid":217400,"title":"Data Modeling Strategies - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Databricks Lakehouse Platform을 사용하여 확장 가능하고 분석에 적합한 데이터 모델을 설계하는 방법을 학습합니다. 이 과정은 기본 데이터 모델링 원칙, 고급 웨어하우징 및 머신 러닝 사용 사례, 최신 데이터 제품 설계를 다루는 3개 모듈로 구성되어 있습니다. Inmon의 CIF, Kimball의 차원 모델링, Data Vault 2.0과 같은 핵심 방법론을 살펴보고, Databricks에서 이러한 전략을 구현하는 방법에 대한 실제 데모도 살펴봅니다.
실습 랩을 통해 ER 다이어그램을 작성하고, SCD 유형 2 변환을 적용하고, ML 워크플로를 위한 특징점을 만듭니다. 또한 이 과정에서는 데이터 제품의 개념을 소개하고 제품 사고, 거버넌스, 의미적 일관성이 어떻게 확장 가능한 교차 도메인 통합을 가능하게 하는지 설명합니다. 이 과정을 마치면 통합된 Lakehouse 아키텍처에서 데이터를 효과적으로 모델링, 관리하고 운영할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28166","entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4561"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/developing-applications-with-apache-spark-korean-4561"}}],"nid":28166,"vid":217471,"title":"Developing Applications with Apache Spark™ - Korean","price":"75.00","duration":10800,"body":{"processed":"이 실습 과정에서 Apache Spark로 확장 가능한 데이터 처리를 마스터하세요. Spark의 DataFrame API를 사용하여 효율적인 ETL 파이프라인을 구축하고, 고급 분석을 수행하며, 분산 데이터 변환을 최적화하는 방법을 알아보세요. 그룹화, 집계, 조인, 집합 연산 및 창 함수를 살펴봅니다. 배열, 맵, 구조체와 같은 복잡한 데이터 유형으로 작업하면서 성능 최적화를 위한 모범 사례를 적용하세요.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28288","entityUrl":{"path":"/kr/training/catalog/agent-evaluation-on-databricks-korean-2858"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/agent-evaluation-on-databricks-korean-2858"}}],"nid":28288,"vid":217593,"title":"Agent Evaluation on Databricks - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 MLflow의 평가 프레임워크를 활용해 AI 에이전트를 체계적으로 평가하는 방법을 가르치며, 전통적인 소프트웨어 테스트가 해결할 수 없는 비결정론적 AI 시스템의 독특한 도전 과제를 다룹니다. 학생들은 올바름과 안전성 같은 공통 기준에 대한 기본 내장 평가자, 사업 구체화 요구사항을 위한 가이드라인 평가자, 그리고 특화된 필요에 맞는 맞춤형 평가자 등 다양한 평가 방식을 구현하는 법을 배웁니다. 이 과정은 엄선된 데이터셋을 이용한 오프라인 평가와 온라인 생산 모니터링을 모두 포함하며, MLflow의 추적 기능을 활용해 에이전트 실행 패턴을 이해하고 다양한 이해관계자 유형으로부터 인간 피드백을 수집하는 실무 경험을 제공합니다. 실습 시연과 실험을 통해 학생들은 AI 에이전트 개발 수명 주기 전반에 걸쳐 지속적인 품질 개선을 이끄는 평가 워크플로우를 만드는 기술을 개발합니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-27T09:00:00"},"endDate":{"value":"2026-10-27T13:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28340","entityUrl":{"path":"/kr/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-korean-3290"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/build-data-pipelines-with-lakeflow-spark-declarative-pipelines-korean-3290"}}],"nid":28340,"vid":217645,"title":"Build Data Pipelines with Lakeflow Spark Declarative Pipelines - Korean","price":"0.00","duration":14400,"body":{"processed":"이 과정에서는 여러 스트리밍 테이블과 구체화된 보기를 통한 증분 배치 또는 스트리밍 수집 및 처리를 위해 Databricks의 Lakeflow 선언적 파이프라인를 사용하여 데이터 파이프라인을 구축하는 데 필요한 필수 개념과 기술을 사용자에게 소개합니다. Lakeflow 선언적 파이프라인를 처음 접하는 데이터 엔지니어를 위해 설계된 이 과정은 증분 데이터 처리, 스트리밍 테이블, 구체화된 보기 및 임시 보기와 같은 핵심 구성 요소에 대한 포괄적인 개요를 제공하고 구체적인 목적과 차이점을 강조합니다.
다루는 주제는 다음과 같습니다.
- SQL을 사용하여 Lakeflow의 다중 파일 편집기로 ETL 파이프라인 개발 및 디버깅 (Python 코드 예제 제공)
- Lakeflow 선언적 파이프라인이 파이프라인 그래프
를 통해 파이프라인의 데이터 종속성을 추적하는 방법- 파이프라인 컴퓨팅 리소스, 데이터 자산, 트리거 모드 및 기타 고급 옵션
구성 다음으로, 이 과정에서는 Lakeflow의 데이터 품질 기대치를 소개하고, 데이터 무결성을 검증하고 적용하기 위해 기대치를 파이프라인에 통합하는 프로세스를 안내합니다. 그런 다음 학습자는 스케줄링 옵션, 프로덕션 모드, 파이프라인 이벤트 로깅을 활성화하여 파이프라인 성능 및 상태를 모니터링하는 등 파이프라인을 프로덕션에 적용하는 방법을 살펴봅니다.
마지막으로, 이 과정에서는 Lakeflow Declarative Pipelines 내에서 APPLY CHANGES INTO 구문을 사용하여 Change Data Capture (CDC)를 구현하여 느리게 변화하는 차원(SCD 유형 1 및 유형 2)을 관리하여 사용자가 CDC를 자신의 파이프라인에 통합할 수 있도록 준비하는 방법을 다룹니다.
참고: 이 과정은 'Databricks을 사용한 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28098","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-4182"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-for-data-warehousing-korean-4182"}}],"nid":28098,"vid":217403,"title":"Get Started with Databricks for Data Warehousing - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정은 Databricks의 현대적인 데이터 웨어하우징 접근 방식에 대한 포괄적이고 실습 중심의 개요를 제공하며, 데이터 레이크하우스 아키텍처가 기존 데이터 웨어하우스의 강점과 클라우드의 유연성 및 확장성을 어떻게 결합하는지를 중점적으로 다룹니다. 가상의 소매업체(Vintage Audio Co.)를 대상으로 엔드투엔드 작업을 수행하면서, 워크스페이스를 탐험하고, 거버넌스가 적용된 Unity Catalog 테이블을 쿼리하며, 분석 읽기를 위해 Unity Catalog 관리형 테이블을 빠르게 유지하고, Auto Loader로 데이터를 증분 로드하고, 스타 스키마를 모델링하며, Unity Catalog 메트릭 뷰를 통해 일관된 인사이트를 제공합니다. 이 모든 작업은 AI 기반 기능(Predictive Optimization, Genie Code)이 전반에 걸쳐 내장된 단일 거버넌스 환경에서 이루어집니다.
Databricks Free Edition 계정을 생성하고 실습 환경에서 따라 해보는 데모를 체험해 보실 수 있습니다.
Languages Available: English | 日本語 | Português BR| 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28167","entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4563"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-korean-4563"}}],"nid":28167,"vid":217472,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 안전한 데이터 거버넌스, 액세스 제어 및 계보 추적을 위한 Unity Catalog에 중점을 두고 확장 가능한 데이터 워크플로를 위한 레이크하우스 아키텍처 및 메달리온 설계를 살펴봅니다. 커리큘럼에는 Delta Lake를 사용하여 신뢰할 수 있는 ACID 호환 파이프라인 구축이 포함됩니다. 파티셔닝, 캐싱, 쿼리 튜닝과 같은 Spark 최적화 기술을 살펴보고 실제 문제를 해결하기 위한 효율적인 데이터 엔지니어링 및 분석을 위한 성능 모니터링, 문제 해결 및 모범 사례를 배웁니다.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28294","entityUrl":{"path":"/kr/training/catalog/data-ingestion-with-lakeflow-connect-korean-2870"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-ingestion-with-lakeflow-connect-korean-2870"}}],"nid":28294,"vid":219018,"title":"Data Ingestion with Lakeflow Connect - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 다양한 소스에서 Databricks로 데이터를 수집하기 위한 확장 가능하고 간소화된 솔루션인 LakeFlow Connect에 대한 포괄적인 입문 내용을 제공합니다. LakeFlow Connect 커넥터의 다양한 유형(Standard 및 Managed)을 탐색하는 것으로 시작하여 배치, 증분 배치, 스트리밍 수집을 포함한 다양한 데이터 수집 기법을 학습합니다. 또한 Delta 테이블과 메달리온 아키텍처 사용의 주요 이점도 살펴봅니다.
다음으로, LakeFlow Connect Standard Connectors를 사용하여 클라우드 오브젝트 스토리지에서 데이터를 수집하는 실용적인 기술을 개발합니다. 여기에는 CREATE TABLE AS SELECT(CTAS), COPY INTO, Auto Loader와 같은 방법을 활용하는 내용이 포함되며, 각 접근 방식의 이점과 고려 사항을 중점적으로 다룹니다. 또한 Databricks Data Intelligence Platform으로 수집하는 과정에서 브론즈 레벨 테이블에 메타데이터 컬럼을 추가하는 방법도 학습합니다. 이어서 rescued data 컬럼을 사용하여 테이블 스키마와 일치하지 않는 레코드를 처리하는 방법과 해당 데이터를 관리 및 분석하는 전략을 다룹니다. 반정형 JSON 데이터를 수집하고 평탄화하는 기법도 살펴봅니다.
그 다음으로, LakeFlow Connect Managed Connectors를 사용하여 데이터베이스 및 SaaS(Software-as-a-Service) 애플리케이션에서 데이터를 가져오는 엔터프라이즈급 데이터 수집을 수행하는 방법을 탐색합니다. 또한 수집 워크로드에 파트너 도구를 통합하기 위한 옵션으로 Partner Connect도 소개합니다.
마지막으로, MERGE INTO 운영 및 Databricks Marketplace 활용을 포함한 대안적 수집 전략으로 과정을 마무리하며, 현대적인 데이터 엔지니어링 사용 사례를 지원하기 위한 탄탄한 기초를 갖출 수 있도록 합니다.
참고: Databricks Academy는 Databricks 환경 내 교실 세션에서 노트북 기반 형식으로 전환하고 있으며, 강의용 슬라이드 덱의 사용을 중단하고 있습니다. Vocareum 실습 환경에서 강의 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
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다루는 주제는 다음과 같습니다.
- SQL을 사용하여 Lakeflow의 다중 파일 편집기로 ETL 파이프라인 개발 및 디버깅 (Python 코드 예제 제공)
- Lakeflow 선언적 파이프라인이 파이프라인 그래프
를 통해 파이프라인의 데이터 종속성을 추적하는 방법- 파이프라인 컴퓨팅 리소스, 데이터 자산, 트리거 모드 및 기타 고급 옵션
구성 다음으로, 이 과정에서는 Lakeflow의 데이터 품질 기대치를 소개하고, 데이터 무결성을 검증하고 적용하기 위해 기대치를 파이프라인에 통합하는 프로세스를 안내합니다. 그런 다음 학습자는 스케줄링 옵션, 프로덕션 모드, 파이프라인 이벤트 로깅을 활성화하여 파이프라인 성능 및 상태를 모니터링하는 등 파이프라인을 프로덕션에 적용하는 방법을 살펴봅니다.
마지막으로, 이 과정에서는 Lakeflow Declarative Pipelines 내에서 APPLY CHANGES INTO 구문을 사용하여 Change Data Capture (CDC)를 구현하여 느리게 변화하는 차원(SCD 유형 1 및 유형 2)을 관리하여 사용자가 CDC를 자신의 파이프라인에 통합할 수 있도록 준비하는 방법을 다룹니다.
Languages Available: English | 日本語 | Português BR | 한국어
이 과정에서는 Databricks SQL에 특히 초점을 맞춰 Databricks를 사용하여 데이터 분석을 효과적으로 수행하는 방법을 학습합니다. Databricks 데이터 애널리스트로서 귀하의 책임에는 관련 데이터를 찾고, 잠재적인 응용 프로그램을 위해 데이터를 분석하고, 귀중한 비즈니스 통찰력을 제공하는 형식으로 데이터를 변환하는 것이 포함됩니다.
또한 Databricks Data Intelligence Platform에서 Notebooks, SQL Editor, Databricks SQL과 같은 도구를 사용하여 데이터 객체를 관리하는 역할과 이를 조작하는 방법을 이해하게 됩니다.
또한, 데이터 자산과 전반적인 플랫폼을 관리하는 데 있어 Unity Catalog의 중요성에 대해서도 알아봅니다. 마지막으로, 이 과정에서는 Databricks가 어떻게 성능 최적화를 용이하게 하는지에 대한 개요를 제공하고, Databricks에서 SQL 분석을 실행할 때 내부적으로 발생하는 프로세스를 이해하기 위해 Query Insights에 액세스하는 방법을 알려드립니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28168","entityUrl":{"path":"/kr/training/catalog/stream-processing-and-analysis-with-apache-spark-korean-4565"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/stream-processing-and-analysis-with-apache-spark-korean-4565"}}],"nid":28168,"vid":217473,"title":"Stream Processing and Analysis with Apache Spark™ - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서 Apache Spark를 사용하여 스트림 처리 및 분석의 기본 사항을 알아보세요.™ 스트림 처리 기본 사항에 대한 확실한 이해를 얻고 Spark Structured Streaming API를 사용하여 애플리케이션을 개발합니다. 스트림 집계 및 창 분석과 같은 고급 기술을 탐색하여 실시간 데이터를 효율적으로 처리하세요. 이 과정에서는 동적 데이터 환경을 위한 확장 가능하고 장애에 강한 스트리밍 애플리케이션을 만드는 기술을 습득합니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2398,"name":"Apache Spark Developer"}},"sessions":[]},{"id":"28297","entityUrl":{"path":"/kr/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-korean-2876"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-korean-2876"}}],"nid":28297,"vid":217602,"title":"Build Data Pipelines with Apache Spark™ Declarative Pipelines - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정은 Databricks에서 Apache Spark™ Declarative Pipelines(SDP)를 사용하여 증분 배치 또는 스트리밍 수집 및 처리를 위한 데이터 파이프라인을 구축하는 데 필요한 핵심 개념과 기술을 사용자에게 소개합니다. 여러 스트리밍 테이블과 구체화된 뷰를 통해 처리 과정을 다룹니다. Spark Declarative Pipelines를 처음 접하는 데이터 엔지니어를 대상으로 설계된 이 과정은 증분 데이터 처리, 스트리밍 테이블, 구체화된 뷰, 임시 뷰 등 핵심 구성 요소에 대한 포괄적인 개요를 제공하며, 각 구성 요소의 목적과 차이점을 중점적으로 설명합니다.
다루는 주제는 다음과 같습니다:
• SQL을 사용하여 Spark Declarative Pipelines의 다중 파일 편집기로 ETL 파이프라인을 개발하고 디버깅하기 (Python 코드 예제 포함)
• Spark Declarative Pipelines가 파이프라인 그래프를 통해 파이프라인 내 데이터 의존성을 추적하는 방법
• 파이프라인 compute 리소스, 데이터 자산, 트리거 모드 및 기타 고급 옵션 구성
다음으로, 이 과정은 Spark Declarative Pipelines의 데이터 품질 기대값을 소개하고, 데이터 무결성을 검증하고 적용하기 위해 파이프라인에 기대값을 통합하는 과정을 안내합니다. 학습자는 스케줄링 옵션 설정, 파이프라인 이벤트 로깅 활성화를 포함하여 파이프라인을 생산 환경에 배포하는 방법을 탐험하고, 파이프라인 성능과 상태를 모니터링하는 방법도 학습합니다.
마지막으로, 이 과정은 Spark Declarative Pipelines 내에서 AUTO CDC INTO 구문을 사용하여 변경 데이터 캡처(CDC)를 구현하고 점진적 변경 차원(SCD Type 1 및 Type 2)을 관리하는 방법을 다루며, 사용자가 자신의 파이프라인에 CDC를 통합할 수 있도록 준비시킵니다.
참고: Databricks Academy는 Databricks 환경 내 강의실 세션을 위해 notebook 기반 형식으로 전환하고 있으며, 강의용 슬라이드 덱 사용을 중단합니다. 강의 notebook은 Vocareum lab 환경에서 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-15T09:00:00"},"endDate":{"value":"2026-10-15T13:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-11-10T14:00:00"},"endDate":{"value":"2026-11-10T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28346","entityUrl":{"path":"/kr/training/catalog/data-ingestion-with-lakeflow-connect-korean-3305"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-ingestion-with-lakeflow-connect-korean-3305"}}],"nid":28346,"vid":217651,"title":"Data Ingestion with Lakeflow Connect - Korean","price":"75.00","duration":14400,"body":{"processed":"이 과정은 데이터 전문가가 Databricks Intelligence Platform을 활용하여 ETL 파이프라인을 생산화할 수 있도록 준비시킵니다. 학생들은 Spark SQL 및 Python과 함께 Delta Live Tables를 사용하여 다양한 데이터 소스의 새로운 데이터를 Lakehouse로 점진적으로 처리하는 파이프라인을 정의하고 예약합니다. 수강생들은 또한 Databricks Workflows를 사용하여 태스크를 오케스트레이션하고 Databricks Repos를 통해 코드를 프로모션합니다.
참고: 이 과정은 'Databricks을 사용한 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28103","entityUrl":{"path":"/kr/training/catalog/sql-analytics-on-databricks-korean-4192"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/sql-analytics-on-databricks-korean-4192"}}],"nid":28103,"vid":217408,"title":"SQL Analytics on Databricks - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks SQL에 특히 초점을 맞춰 Databricks를 사용하여 데이터 분석을 효과적으로 수행하는 방법을 학습합니다. Databricks 데이터 애널리스트로서 귀하의 책임에는 관련 데이터를 찾고, 잠재적인 응용 프로그램을 위해 데이터를 분석하고, 귀중한 비즈니스 통찰력을 제공하는 형식으로 데이터를 변환하는 것이 포함됩니다.
또한 Databricks Data Intelligence Platform에서 Notebooks, SQL Editor, Databricks SQL과 같은 도구를 사용하여 데이터 객체를 관리하는 역할과 이를 조작하는 방법을 이해하게 됩니다.
또한, 데이터 자산과 전반적인 플랫폼을 관리하는 데 있어 Unity Catalog의 중요성에 대해서도 알아봅니다. 마지막으로, 이 과정에서는 Databricks가 어떻게 성능 최적화를 용이하게 하는지에 대한 개요를 제공하고, Databricks에서 SQL 분석을 실행할 때 내부적으로 발생하는 프로세스를 이해하기 위해 Query Insights에 액세스하는 방법을 알려드립니다.
Languages Available: English | 日本語 | Português BR | 한국어
이 과정에서 Apache Spark를 사용하여 스트림 처리 및 분석의 기본 사항을 알아보세요.™ 스트림 처리 기본 사항에 대한 확실한 이해를 얻고 Spark Structured Streaming API를 사용하여 애플리케이션을 개발합니다. 스트림 집계 및 창 분석과 같은 고급 기술을 탐색하여 실시간 데이터를 효율적으로 처리하세요. 이 과정에서는 동적 데이터 환경을 위한 확장 가능하고 장애에 강한 스트리밍 애플리케이션을 만드는 기술을 습득합니다.
Languages Available: English | 日本語 | 한국어
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• 방향성 비순환 그래프(DAG)를 사용하여 데이터 워크로드를 설계 및 구현하고, 다양한 스케줄링 옵션을 구성하며, 조건부 태스크 실행, 실행 조건 의존성, for each 루프와 같은 고급 워크플로 기능을 구현하는 방법을 학습합니다.
• 본 과정에서는 적절한 compute 선택, 모듈식 오케스트레이션, 오류 처리 기법, 내결함성 설계를 통해 견고하고 생산 준비가 완료된 파이프라인을 생성하기 위한 모범 사례를 다루며, 이 모든 것이 Databricks Data Intelligence Platform 내에 기본적으로 통합되어 있습니다.
참고: Databricks Academy는 Databricks 환경 내의 대면 강의 형식을 노트북 기반 방식으로 전환함에 따라, 강의용 슬라이드 사용이 중단됩니다. Vocareum 랩 환경에서 강의용 노트북에 액세스할 수 있습니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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참고: 이 과정은 'Databricks을 사용한 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28118","entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4229"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4229"}}],"nid":28118,"vid":217423,"title":"Data Modeling Strategies - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks Lakehouse Platform을 사용하여 확장 가능하고 분석에 적합한 데이터 모델을 설계하는 방법을 학습합니다. 이 과정은 기본 데이터 모델링 원칙, 고급 웨어하우징 및 머신 러닝 사용 사례, 최신 데이터 제품 설계를 다루는 3개 모듈로 구성되어 있습니다. Inmon의 CIF, Kimball의 차원 모델링, Data Vault 2.0과 같은 핵심 방법론을 살펴보고, Databricks에서 이러한 전략을 구현하는 방법에 대한 실제 데모도 살펴봅니다.
실습 랩을 통해 ER 다이어그램을 작성하고, SCD 유형 2 변환을 적용하고, ML 워크플로를 위한 특징점을 만듭니다. 또한 이 과정에서는 데이터 제품의 개념을 소개하고 제품 사고, 거버넌스, 의미적 일관성이 어떻게 확장 가능한 교차 도메인 통합을 가능하게 하는지 설명합니다. 이 과정을 마치면 통합된 Lakehouse 아키텍처에서 데이터를 효과적으로 모델링, 관리하고 운영할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28175","entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-platform-administration-korean-4596"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/get-started-with-databricks-platform-administration-korean-4596"}}],"nid":28175,"vid":217480,"title":"Get Started with Databricks Platform Administration - Korean","price":"75.00","duration":10800,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform의 기본적인 플랫폼 관리 방법을 학습하게 됩니다. Databricks 환경 내에서 효과적인 데이터 거버넌스를 위한 핵심 구성 요소인 Unity Catalog에 대한 포괄적인 개요를 제공합니다. 다섯 개의 모듈로 구성된 이 과정은 Databricks 인프라와 data intelligence platform에 대한 상세한 소개로 시작하며, Databricks Workspace에 대한 심층적인 안내를 포함합니다. Unity Catalog 내 데이터 거버넌스 원칙을 탐구하며 핵심 개념, 아키텍처 및 역할을 다룹니다. 또한 Unity Catalog 메타스토어와 클러스터 및 SQL 웨어하우스를 포함한 compute 리소스 관리에 중점을 둡니다. 마지막으로 권한, 세분화된 접근 제어, 데이터 객체 거버넌스 방법을 학습하여 데이터 접근 제어를 숙달하게 됩니다. 과정을 마치면 효과적인 데이터 거버넌스 구현, 컴퓨팅 자원 최적화, 강력한 데이터 보안 전략 적용을 위한 유니티 카탈로그 관리 필수 기술을 습득하게 됩니다. Databricks Labs 구독 구매 시, 실제 Databricks Workspace 환경에서 배운 내용을 실습할 수 있는 포괄적인 랩 연습으로 과정을 마무리합니다.
Languages Available: English | 日本語 | Português BR | 한국어
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아래에서는 이 과정에 포함된 4개의 4시간짜리 모듈을 각각 설명합니다.
참고: 다음 4개 모듈의 경우, Databricks Academy는 Databricks 환경 내 강의실 세션을 위해 notebook 기반 형식으로 전환하고 있으며, 강의용 슬라이드 덱 사용을 중단합니다. 강의 notebook은 Vocareum lab 환경에서 액세스할 수 있습니다.
1. Data Ingestion with Lakeflow Connect
이 과정에서는 다양한 소스로부터 Databricks로 데이터를 수집하기 위한 확장 가능하고 간소화된 솔루션인 Lakeflow Connect를 종합적으로 소개합니다. 먼저 Lakeflow Connect 커넥터의 다양한 유형(Standard 및 Managed)을 살펴보고 배치, 증분 배치, 스트리밍 수집을 비롯한 여러 데이터 수집 기법을 학습합니다. 또한 Delta table과 Medallion 아키텍처 사용의 주요 이점도 검토합니다.
다음으로, Lakeflow Connect Standard Connectors를 사용하여 클라우드 오브젝트 스토리지에서 데이터를 수집하는 실용적인 기술을 개발합니다. 여기에는 CREATE TABLE AS SELECT (CTAS), COPY INTO, Auto Loader와 같은 방법을 다루며, 각 접근 방식의 이점과 고려 사항에 중점을 둡니다. 또한 Databricks Data Intelligence Platform으로 수집하는 동안 bronze 수준 테이블에 메타데이터 열을 추가하는 방법도 학습합니다. 이어서 rescued data 열을 사용하여 테이블 스키마와 일치하지 않는 레코드를 처리하는 방법과 이러한 데이터를 관리하고 분석하는 전략을 다룹니다. 또한 반정형 JSON 데이터를 수집하고 평면화하는 기법도 살펴봅니다.
그다음에는 Lakeflow Connect Managed Connectors를 사용하여 데이터베이스와 Software-as-a-Service (SaaS) 애플리케이션에서 데이터를 가져오는 엔터프라이즈급 데이터 수집을 수행하는 방법을 살펴봅니다. 또한 파트너 도구를 수집 워크로드에 통합하는 옵션으로 Partner Connect를 소개합니다.
마지막으로, MERGE INTO 작업과 Databricks Marketplace 활용을 비롯한 대체 수집 전략으로 과정을 마무리하며, 최신 데이터 엔지니어링 사용 사례를 지원하는 탄탄한 기반을 갖추게 됩니다.
2. Deploy Workloads with Lakeflow Jobs
Deploy Workloads with Lakeflow Jobs 과정에서는 Databricks 에코시스템 내의 통합 오케스트레이션 플랫폼인 Lakeflow Jobs를 사용하여 데이터, 분석, AI 워크플로를 오케스트레이션하고 자동화하는 방법을 학습합니다.
• 방향성 비순환 그래프(DAG)를 사용하여 데이터 워크로드를 설계 및 구현하고, 다양한 스케줄링 옵션을 구성하며, 조건부 작업 실행, run-if 종속성, for each 루프와 같은 고급 워크플로 기능을 구현하는 방법을 학습합니다.
• 이 과정에서는 적절한 컴퓨트 선택, 모듈식 오케스트레이션, 오류 처리 기법, 내결함성 설계를 갖춘 견고하고 프로덕션에 적합한 파이프라인을 만들기 위한 모범 사례를 다루며, 이 모든 것은 Databricks Data Intelligence Platform에 기본적으로 통합되어 있습니다.
3. Build Data Pipelines with Apache Spark Declarative Pipelines
이 과정에서는 Databricks의 Apache Spark Declarative Pipelines (SDP)를 사용하여 여러 스트리밍 테이블과 구체화된 뷰를 통한 증분 배치 또는 스트리밍 수집 및 처리를 위한 데이터 파이프라인을 구축하는 데 필요한 필수 개념과 기술을 소개합니다. Spark Declarative Pipelines를 처음 접하는 데이터 엔지니어를 위해 설계된 이 과정은 증분 데이터 처리, 스트리밍 테이블, 구체화된 뷰, 임시 뷰와 같은 핵심 구성 요소를 종합적으로 개괄하고 각각의 구체적인 목적과 차이점을 강조합니다.
다루는 주제는 다음과 같습니다.
• SQL을 사용하여 Spark Declarative Pipelines의 다중 파일 편집기로 ETL 파이프라인 개발 및 디버깅(Python 코드 예제 제공)
• Spark Declarative Pipelines가 파이프라인 그래프를 통해 파이프라인 내 데이터 종속성을 추적하는 방식
• 파이프라인 컴퓨트 리소스, 데이터 자산, 트리거 모드 및 기타 고급 옵션 구성
다음으로, Spark Declarative Pipelines의 데이터 품질 기대치(expectations)를 소개하고, 데이터 무결성을 검증하고 적용하기 위해 기대치를 파이프라인에 통합하는 과정을 안내합니다. 이후 학습자는 스케줄링 옵션을 포함하여 파이프라인을 프로덕션에 배포하는 방법과, 파이프라인 성능 및 상태를 모니터링하기 위한 파이프라인 이벤트 로깅 활성화 방법을 살펴봅니다.
마지막으로, 이 과정에서는 Spark Declarative Pipelines 내에서 AUTO CDC INTO 구문을 사용하여 Change Data Capture (CDC)를 구현해 천천히 변화하는 차원(SCD Type 1 및 Type 2)을 관리하는 방법을 다루며, 학습자가 CDC를 자신의 파이프라인에 통합할 수 있도록 준비시킵니다.
4. DevOps Essentials for Data Engineering
이 과정에서는 Databricks로 작업하는 데이터 엔지니어를 위해 특별히 설계된 소프트웨어 엔지니어링 모범 사례와 DevOps 원칙을 살펴봅니다. 참석자는 코드 품질, 버전 관리, 문서화, 테스트와 같은 핵심 주제에 대한 탄탄한 기반을 구축합니다. 이 과정은 DevOps에 중점을 두어 핵심 구성 요소, 이점, 그리고 데이터 엔지니어링 워크플로를 최적화하는 데 있어 지속적 통합 및 배포(CI/CD)의 역할을 다룹니다.
재사용 가능한 구성 요소를 만들고 코드를 효율적으로 구조화하기 위해 PySpark에서 모듈성 원칙을 적용하는 방법을 학습합니다. 실습에는 pytest 프레임워크를 사용하여 PySpark 함수에 대한 단위 테스트를 설계하고 구현한 다음, 신뢰성을 보장하기 위해 Spark Declarative Pipeline 및 Jobs를 사용하여 Databricks 데이터 파이프라인에 대한 통합 테스트를 수행하는 과정이 포함됩니다.
또한 이 과정에서는 지속적 통합 관행을 통합하기 위한 Databricks Git Folders 사용을 비롯하여 Databricks 내의 필수 Git 작업을 다룹니다. 마지막으로 REST API, CLI, SDK, Declarative Automation Bundles (DABs)와 같은 Databricks 자산의 다양한 배포 방법을 개괄적으로 살펴봄으로써 파이프라인을 배포하고 관리하는 기법에 대한 지식을 갖추게 됩니다.
과정을 마치면 소프트웨어 엔지니어링 및 DevOps 모범 사례에 능숙해져 확장 가능하고 유지 관리가 용이하며 효율적인 데이터 엔지니어링 솔루션을 구축할 수 있게 됩니다.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-13T09:00:00"},"endDate":{"value":"2026-10-14T17:00:00"},"timezone":"Asia/Seoul"}},{"entity":{"startDate":{"value":"2026-11-02T09:00:00"},"endDate":{"value":"2026-11-03T17:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28349","entityUrl":{"path":"/kr/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-korean-3348"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-korean-3348"}}],"nid":28349,"vid":217654,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Korean","price":"75.00","duration":14400,"body":{"processed":"이 과정은 Spark Structured Streaming과 Delta Lake에 대한 포괄적인 이해를 제공하며, 여기에는 계산 모델, 스트리밍 읽기 구성, 스트리밍 환경에서의 데이터 품질 유지 관리 등이 포함됩니다.
참고: 이 과정은 'Databricks을 사용한 고급 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28121","entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4233"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/data-modeling-strategies-korean-4233"}}],"nid":28121,"vid":217426,"title":"Data Modeling Strategies - Korean","price":"0.00","duration":7200,"body":{"processed":"이 과정에서는 Databricks Lakehouse Platform을 사용하여 확장 가능하고 분석에 적합한 데이터 모델을 설계하는 방법을 학습합니다. 이 과정은 기본 데이터 모델링 원칙, 고급 웨어하우징 및 머신 러닝 사용 사례, 최신 데이터 제품 설계를 다루는 3개 모듈로 구성되어 있습니다. Inmon의 CIF, Kimball의 차원 모델링, Data Vault 2.0과 같은 핵심 방법론을 살펴보고, Databricks에서 이러한 전략을 구현하는 방법에 대한 실제 데모도 살펴봅니다.
실습 랩을 통해 ER 다이어그램을 작성하고, SCD 유형 2 변환을 적용하고, ML 워크플로를 위한 특징점을 만듭니다. 또한 이 과정에서는 데이터 제품의 개념을 소개하고 제품 사고, 거버넌스, 의미적 일관성이 어떻게 확장 가능한 교차 도메인 통합을 가능하게 하는지 설명합니다. 이 과정을 마치면 통합된 Lakehouse 아키텍처에서 데이터를 효과적으로 모델링, 관리하고 운영할 수 있는 역량을 갖추게 됩니다.
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28184","entityUrl":{"path":"/kr/training/catalog/databricks-platform-administration-fundamentals-korean-4651"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-platform-administration-fundamentals-korean-4651"}}],"nid":28184,"vid":217489,"title":"Databricks Platform Administration Fundamentals - Korean","price":"0.00","duration":5400,"body":{"processed":"이 과정에서는 Databricks Data Intelligence Platform에서 플랫폼 관리의 기초를 배웁니다. Databricks 아키텍처, 보안 모델, 관리 역할, 클라우드 리소스 관리 및 자동화 기술을 다룹니다. 워크스페이스, 메타스토어 및 외부 스토리지 관리를 포함한 주요 관리 책임을 살펴보고 액세스 제어 및 역할 기반 권한을 통해 보안을 보장합니다. 또한 Databricks SDK, CLI 및 Terraform를 사용하여 관리 작업을 자동화하는 방법을 배웁니다. 이 과정에는 개념을 강화하고 플랫폼 관리를 간소화하기 위한 실습 데모가 포함되어 있습니다. 결국에는 조직의 Databricks 환경을 효율적으로 관리, 보호 및 자동화할 수 있도록 준비가 됩니다.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28313","entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-2980"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-2980"}}],"nid":28313,"vid":217618,"title":"Databricks Performance Optimization - Korean","price":"750.00","duration":14400,"body":{"processed":"이 과정에서는 Spark와 Delta Lake를 활용해 워크로드와 물리적 레이아웃을 최적화하는 방법을 배우고, Spark UI를 분석하여 성능을 평가하고 애플리케이션을 디버깅하는 방법을 익히게 됩니다. 스트리밍, 유동적 클러스터링, 데이터 스키핑, 캐싱, 포토네이션 등 다양한 주제를 다룰 예정입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-24T14:00:00"},"endDate":{"value":"2026-11-24T18:00:00"},"timezone":"Asia/Seoul"}}]},{"id":"28352","entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-3370"},"entityTranslations":[{"entityLanguage":{"id":"ko"},"entityUrl":{"path":"/kr/training/catalog/databricks-performance-optimization-korean-3370"}}],"nid":28352,"vid":217657,"title":"Databricks Performance Optimization - Korean","price":"75.00","duration":14400,"body":{"processed":"이 과정에서는 Spark와 Delta Lake를 활용해 워크로드와 물리적 레이아웃을 최적화하는 방법을 배우고, Spark UI를 분석하여 성능을 평가하고 애플리케이션을 디버깅하는 방법을 익히게 됩니다. 스트리밍, 유동적 클러스터링, 데이터 스키핑, 캐싱, 포토네이션 등 다양한 주제를 다룰 예정입니다.
메모: 이 과정은 'Databrick을 사용한 고급 데이터 엔지니어링' 과정 시리즈의 일부입니다.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]}]},"coursesBR":{"entities":[{"id":"33956","entityUrl":{"path":"/br/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-portuguese-br-6643"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-portuguese-br-6643"}}],"nid":33956,"vid":254346,"title":"Building Databricks Apps with Genie Code and Lakebase - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps possibilita criar e implantar aplicações interativas de dados e IA diretamente na plataforma Databricks. Mas o desenvolvimento assistido por IA bem-sucedido vai além da geração de código — trata-se de desenvolver um fluxo de trabalho eficaz.
Neste curso prático, você criará um Databricks App com suporte do Lakebase do zero, utilizando o Genie Code como seu assistente de desenvolvimento com IA. Ao longo do caminho, você aprenderá uma abordagem prática e repetível para o desenvolvimento assistido por IA: especificar claramente a intenção antes de gerar código, trabalhar em incrementos pequenos e verificáveis, aproveitar as Genie Code Skills reutilizáveis e tratar o resultado gerado pela IA como algo a ser revisado e refinado — e não simplesmente aceito.
Você criará e implantará um Databricks App, provisionará e conectará um banco de dados Lakebase como seu armazenamento transacional, implementará operações CRUD e usará o Genie Code para acelerar tarefas comuns de desenvolvimento. Ao final do curso, você não apenas terá uma aplicação funcional, mas também um Framework prático para colaborar de forma eficaz com a IA em futuros projetos de software.
Observação: a Databricks Academy está migrando as sessões em sala de aula no ambiente Databricks para um formato baseado em notebooks e deixando de usar apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de laboratório do Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33961","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4629"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4629"}}],"nid":33961,"vid":254352,"title":"Get Started with Databricks Platform Administration - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você aprenderá os conceitos básicos de administração de plataforma no Databricks Data Intelligence Platform. Ele oferece uma visão geral abrangante do Unity Catalog, um componente vital para uma governança de dados eficaz em ambientes Databricks. Dividido em cinco módulos, ele começa com uma introdução detalhada à infraestrutura Databricks e sua data intelligence platform, incluindo um passo a passo detalhado do Databricks Workspace. Você explorará os princípios de governança de dados dentro do Unity Catalog, abordando seus principais conceitos, arquitetura e funções. O curso enfatiza ainda o gerenciamento de metastores Unity Catalog e recursos de compute, incluindo clusters e warehouses SQL. Por fim, você dominará o controle de acesso a dados aprendendo sobre privilégios, acesso refinado e como controlar objetos de dados. Ao final, você estará equipado com habilidades essenciais para administrar o Unity Catalog para implementar uma governança de dados eficaz, otimizar recursos de compute e aplicar estratégias robustas de segurança de dados. Com a compra de uma assinatura Databricks Labs, o curso também se encerra com um exercício de laboratório abrangente para praticar o que você aprendeu em um ambiente Databricks Workspace ao vivo.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"33900","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3782"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3782"}}],"nid":33900,"vid":254035,"title":"Get Started with Databricks for Generative AI - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece uma introdução prática ao Databricks Data Intelligence Platform, com foco em seus principais componentes e recursos para criação e implantação de sistemas de IA generativa. Os participantes aprenderão como o Databricks facilita o desenvolvimento de soluções escaláveis de IA generativa e explorarão ferramentas como AI Search, o Agent Framework e as capacidades de IA generativa do MLflow para acompanhamento e registro de modelos. Este curso inclui experiência prática na construção e avaliação de pipelines de Retrieval-Augmented Generation (RAG), implantação de agentes de IA generativa e uso de frameworks de avaliação para otimizar o desempenho. Ao final do curso, os alunos estarão equipados com as habilidades necessárias para projetar, implantar e monitorar aplicações comuns de IA generativa no Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33901","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3783"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3783"}}],"nid":33901,"vid":254036,"title":"Get Started with Databricks for Generative AI - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso oferece uma introdução prática ao Databricks Data Intelligence Platform, com foco em seus principais componentes e recursos para criação e implantação de sistemas de IA generativa. Os participantes aprenderão como o Databricks facilita o desenvolvimento de soluções escaláveis de IA generativa e explorarão ferramentas como AI Search, o Agent Framework e as capacidades de IA generativa do MLflow para acompanhamento e registro de modelos. Este curso inclui experiência prática na construção e avaliação de pipelines de Retrieval-Augmented Generation (RAG), implantação de agentes de IA generativa e uso de frameworks de avaliação para otimizar o desempenho. Ao final do curso, os alunos estarão equipados com as habilidades necessárias para projetar, implantar e monitorar aplicações comuns de IA generativa no Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어 | 普通话 | Français | Español
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33833","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3518"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3518"}}],"nid":33833,"vid":253553,"title":"Get Started with Databricks for Machine Learning - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você aprenderá habilidades básicas que permitirão utilizar o Databricks Data Intelligence Platform para executar um fluxo de trabalho simples de ciência de dados e machine learning. Você receberá um tour pelo workspace e aprenderá a trabalhar com Notebooks. Você irá explorar análise exploratória de dados e Engenharia de Recursos, rastrear e gerenciar modelos com MLflow, experimentar usando Databricks Genie Code e implantar um modelo com Databricks Model Serving. Por fim, o curso reúne essas habilidades em um laboratório abrangente que cobre o fluxo de trabalho de machine learning de ponta a ponta.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-19T09:00:00"},"endDate":{"value":"2026-11-19T11:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"33817","entityUrl":{"path":"/br/training/catalog/apache-spark-programming-with-databricks-portuguese-br-6457"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/apache-spark-programming-with-databricks-portuguese-br-6457"}}],"nid":33817,"vid":253384,"title":"Apache Spark Programming with Databricks - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Este é um curso introdutório que serve como um ponto de entrada adequado para aprender Data Engineering com o Databricks.
A seguir, descrevemos cada um dos quatro módulos de quatro horas incluídos neste curso.
Nota: para os quatro módulos a seguir, a Databricks Academy está migrando para um formato baseado em notebooks nas sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de lab do Vocareum.
Introduction to Apache Spark
Este curso introdutório aborda os fundamentos do Apache Spark para processamento de dados em larga escala. Você irá explorar a arquitetura distribuída do Spark, dominar a DataFrame API e aprender a ler, gravar e processar dados usando Python. Por meio de exercícios práticos, você desenvolverá as habilidades necessárias para executar transformações e ações do Spark com eficiência.
Developing Applications with Apache Spark
Domine o processamento escalável de dados com Apache Spark neste curso. Aprenda a construir pipelines ETL eficientes, realizar analítica avançada e otimizar transformações de dados distribuídos usando a DataFrame API do Spark. Explore agrupamentos, agregações, junções, operações de conjuntos e funções de janela. Trabalhe com tipos de dados complexos como arrays, mapas e structs, aplicando as melhores práticas para otimização de desempenho.
Stream Processing and Analysis with Apache Spark
Este curso orienta os alunos sobre como desenvolver aplicações de processamento de transmissão escaláveis e tolerantes a falhas usando a API Spark Structured Streaming no Databricks.
Monitoring and Optimizing Apache Spark Workloads on Databricks
Este curso abrange os principais componentes do Databricks platform e do Apache Spark com Delta Lake, com foco na arquitetura Lakehouse, no Unity Catalog e em técnicas de gestão de dados como transações ACID e manutenção de tabelas. Além disso, ensina os alunos a otimizar o desempenho de query por meio de particionamento, shuffles e ferramentas de ajuste, ao mesmo tempo em que utiliza o Spark UI para monitorar aplicações e resolver gargalos.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33812","entityUrl":{"path":"/br/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-portuguese-br-6555"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-portuguese-br-6555"}}],"nid":33812,"vid":253350,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso abrange os principais componentes do Databricks platform e do Apache Spark com Delta Lake, com foco na arquitetura Lakehouse, no Unity Catalog e em técnicas de gestão de dados como transações ACID e manutenção de tabelas. Além disso, ensina os alunos a otimizar o desempenho de query por meio de particionamento, shuffles e ferramentas de ajuste, ao mesmo tempo em que utiliza o Spark UI para monitorar aplicações e resolver gargalos.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33806","entityUrl":{"path":"/br/training/catalog/stream-processing-and-analysis-with-apache-spark-portuguese-br-6546"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/stream-processing-and-analysis-with-apache-spark-portuguese-br-6546"}}],"nid":33806,"vid":253321,"title":"Stream Processing and Analysis with Apache Spark - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso orienta os alunos sobre como desenvolver aplicações de processamento de transmissão escaláveis e tolerantes a falhas usando a API Spark Structured Streaming no Databricks.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 |한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33340","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6521"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6521"}}],"nid":33340,"vid":252747,"title":"Get Started with Databricks: End to End - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso é uma introdução abrangente e prática ao Databricks Data Intelligence Platform. Você seguirá uma jornada completa de ponta a ponta que começa no workspace e termina com uma introdução à IA e machine learning, abordando as habilidades do dia a dia necessárias para trabalhar com dados no Databricks.
O curso abrange:
Ao final do curso, você estará confortável para navegar pelo Databricks, encontrar e governar dados no Unity Catalog, escrever código SQL e em notebook com assistência de IA, criar painéis e explorar dados com o Genie.
Observação: para arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão “Next Lesson”, pois isso pode impedir que o módulo SCORM seja marcado como concluído.
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33341","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6522"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6522"}}],"nid":33341,"vid":252748,"title":"Get Started with Databricks: End to End - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso é uma introdução abrangente e prática ao Databricks Data Intelligence Platform. Você seguirá uma jornada completa de ponta a ponta que começa no workspace e termina com uma introdução à IA e machine learning, abordando as habilidades do dia a dia necessárias para trabalhar com dados no Databricks.
O curso abrange:
Ao final do curso, você estará confortável para navegar pelo Databricks, encontrar e governar dados no Unity Catalog, escrever código SQL e em notebook com assistência de IA, criar painéis e explorar dados com o Genie.
Observação: para arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão “Next Lesson”, pois isso pode impedir que o módulo SCORM seja marcado como concluído.
Languages Available: English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33346","entityUrl":{"path":"/br/training/catalog/developing-applications-with-apache-spark-portuguese-br-6531"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/developing-applications-with-apache-spark-portuguese-br-6531"}}],"nid":33346,"vid":252753,"title":"Developing Applications with Apache Spark - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Domine o processamento escalável de dados com Apache Spark neste curso. Aprenda a construir pipelines ETL eficientes, realizar analítica avançada e otimizar transformações de dados distribuídos usando a DataFrame API do Spark. Explore agrupamentos, agregações, junções, operações de conjuntos e funções de janela. Trabalhe com tipos de dados complexos como arrays, mapas e structs, aplicando as melhores práticas para otimização de desempenho.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33319","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6495"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6495"}}],"nid":33319,"vid":252682,"title":"Get Started with Databricks Apps - Portuguese BR","price":"75.00","duration":7200,"body":{"processed":"Este curso apresenta o Databricks Apps, um recurso que capacita desenvolvedores a criar e implantar aplicações seguras de dados e IA diretamente na plataforma Databricks. É destinado principalmente a cientistas de dados, engenheiros de dados e desenvolvedores que precisam criar aplicações personalizadas que tornem os insights de dados acessíveis a usuários não técnicos dentro de suas organizações.
O curso oferece uma visão geral dos principais componentes do Databricks Apps, seguida pela implantação de aplicações simples que se integram a um serviço externo, bem como a um recurso do Databricks.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33318","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6490"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6490"}}],"nid":33318,"vid":252681,"title":"Get Started with Databricks Apps - Portuguese BR","price":"0.00","duration":3600,"body":{"processed":"Este curso apresenta o Databricks Apps, um recurso que capacita desenvolvedores a criar e implantar aplicações seguras de dados e IA diretamente na plataforma Databricks. É destinado principalmente a cientistas de dados, engenheiros de dados e desenvolvedores que precisam criar aplicações personalizadas que tornem os insights de dados acessíveis a usuários não técnicos dentro de suas organizações.
O curso oferece uma visão geral dos principais componentes do Databricks Apps, seguida pela implantação de aplicações simples que se integram a um serviço externo, bem como a um recurso do Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32118","entityUrl":{"path":"/br/training/catalog/ai-agent-fundamentals-accreditation-portuguese-br-4741"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/ai-agent-fundamentals-accreditation-portuguese-br-4741"}}],"nid":32118,"vid":251045,"title":"AI Agent Fundamentals Accreditation - Portuguese BR","price":"0.00","duration":1800,"body":{"processed":"Bem-vindo ao questionário de certificação sobre os fundamentos dos agentes de IA. Neste questionário de 20 perguntas, testaremos seus conhecimentos sobre os fundamentos dos agentes de IA, suas aplicações empresariais e como criá-los e implantá-los usando o Mosaic AI e o Agent Bricks da Databricks. Ao concluir este questionário com sucesso, você receberá um selo (em até 48 horas) por meio de nosso fornecedor de selos, a Accredible. Boa sorte!
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32083","entityUrl":{"path":"/br/training/catalog/databricks-fundamentals-portuguese-br-2299"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-fundamentals-portuguese-br-2299"}}],"nid":32083,"vid":250711,"title":"Databricks Fundamentals - Portuguese BR","price":"0.00","duration":3600,"body":{"processed":"Este curso é uma introdução fundamental ao Databricks e ao Databricks Platform. Você será apresentado aos problemas que as equipes modernas de dados e IA enfrentam, à ideia de lakehouse no centro da plataforma, aos produtos e capacidades que a plataforma oferece, a como ela mantém os dados e a IA confiáveis por meio de governança unificada, e a um tour guiado pelo próprio workspace.
Esses vídeos são disponibilizados em uma ordem sugerida, mas você pode assisti-los na ordem que preferir. Além disso, recomendamos que você assista a todo o conteúdo em vídeo disponível antes de tentar a avaliação de credenciamento do Databricks Fundamentals.
Não assumimos nenhum conhecimento técnico prévio do Databricks ou de plataformas de dados.
.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32045","entityUrl":{"path":"/br/training/catalog/generative-ai-fundamentals-portuguese-br-2252"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/generative-ai-fundamentals-portuguese-br-2252"}}],"nid":32045,"vid":250263,"title":"Generative AI Fundamentals - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Generative AI passou de experimento emergente a capacidade empresarial essencial, impulsionando tudo, desde suporte inteligente ao cliente até agentes de IA que automatizam Workflows complexos.
As organizações que entendem como implantá-la de forma eficaz — fundamentadas em seus próprios dados e governadas para gerar confiança — serão as que definirão o ritmo em suas indústrias. Mas com novos modelos sendo lançados semanalmente e capacidades evoluindo rapidamente, saber como avaliar e Aplicar GenAI de forma estratégica importa mais do que perseguir o lançamento mais recente. Atualize-se sobre os fundamentos de Generative AI — o que ela pode fazer, onde entrega valor real para os negócios e como implementá-la com segurança no Databricks — com este treinamento gratuito sob demanda.
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32032","entityUrl":{"path":"/br/training/catalog/introduction-to-apache-spark-portuguese-br-6460"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/introduction-to-apache-spark-portuguese-br-6460"}}],"nid":32032,"vid":250181,"title":"Introduction to Apache Spark - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso introdutório aborda os fundamentos do Apache Spark para processamento de dados em larga escala. Você irá explorar a arquitetura distribuída do Spark, dominar a DataFrame API e aprender a ler, gravar e processar dados usando Python. Por meio de exercícios práticos, você desenvolverá as habilidades necessárias para executar transformações e ações do Spark com eficiência.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31922","entityUrl":{"path":"/br/training/catalog/ai-agent-fundamentals-portuguese-br-4742"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/ai-agent-fundamentals-portuguese-br-4742"}}],"nid":31922,"vid":250014,"title":"AI Agent Fundamentals - Portuguese BR","price":"0.00","duration":5400,"body":{"processed":"Este curso introdutório apresenta os agentes de IA e seu uso em aplicações empresariais no Databricks, incluindo a plataforma Mosaic AI e o Agent Bricks. Os participantes irão examinar o que são agentes de IA, como funcionam e como imitam o raciocínio humano para lidar com tarefas complexas.
O curso aborda casos de uso reais de agentes e fornece uma introdução básica a tópicos avançados, como Workflows agênticos e sistemas multiagentes. Também explora como o Agent Bricks simplifica o desenvolvimento de agentes prontos para uso empresarial em diversas aplicações, com demonstrações mostrando como construir e utilizar agentes no Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31911","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-6447"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-6447"}}],"nid":31911,"vid":249974,"title":"Get Started with Databricks for Data Warehousing - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece uma visão geral abrangente e prática da abordagem moderna do Databricks para data warehousing, destacando como uma arquitetura data lakehouse combina os pontos fortes dos data warehouses tradicionais com a flexibilidade e escalabilidade do cloud. Trabalhando de ponta a ponta com um varejista fictício (Vintage Audio Co.), você irá explorar o workspace, executar queries em tabelas governadas do Unity Catalog, manter as tabelas gerenciadas do Unity Catalog otimizadas para leituras analíticas, carregar dados de forma incremental com o Auto Loader, modelar um esquema estrela e entregar insights consistentes por meio de visualizações de métricas do Unity Catalog — tudo isso em um único ambiente governado, com recursos orientados por IA (Predictive Optimization, Genie Code) integrados ao longo de todo o processo.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31912","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-6448"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-6448"}}],"nid":31912,"vid":249975,"title":"Get Started with Databricks for Data Warehousing - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso oferece uma visão geral abrangente e prática da abordagem moderna do Databricks para data warehousing, destacando como uma arquitetura data lakehouse combina os pontos fortes dos data warehouses tradicionais com a flexibilidade e escalabilidade do cloud. Trabalhando de ponta a ponta com um varejista fictício (Vintage Audio Co.), você irá explorar o workspace, executar queries em tabelas governadas do Unity Catalog, manter as tabelas gerenciadas do Unity Catalog otimizadas para leituras analíticas, carregar dados de forma incremental com o Auto Loader, modelar um esquema estrela e entregar insights consistentes por meio de visualizações de métricas do Unity Catalog — tudo isso em um único ambiente governado, com recursos orientados por IA (Predictive Optimization, Genie Code) integrados ao longo de todo o processo.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31903","entityUrl":{"path":"/br/training/catalog/data-governance-at-scale-portuguese-br-6426"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-governance-at-scale-portuguese-br-6426"}}],"nid":31903,"vid":249940,"title":"Data Governance at Scale - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá como implementar governança de dados em escala no Databricks usando o Unity Catalog, com foco em controle de acesso baseado em atributos, observabilidade e compartilhamento federado. Você irá configurar o ABAC com tags governadas, migrar de controles legados de granularidade fina, habilitar e usar tabelas de sistema para auditoria e monitoramento de custos, implantar o Data Quality Monitoring para qualidade de dados e modelos, interpretar a linhagem para impacto e compliance, e aplicar padrões de governança federada e Delta Sharing para colaboração segura entre clouds.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31863","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6402"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-end-to-end-portuguese-br-6402"}}],"nid":31863,"vid":249281,"title":"Get Started with Databricks: End to End - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso é uma introdução abrangente e prática ao Databricks Data Intelligence Platform. Você seguirá uma jornada completa de ponta a ponta que começa no workspace e termina com uma introdução à IA e machine learning, abordando as habilidades do dia a dia necessárias para trabalhar com dados no Databricks.
O curso abrange:
• Navegação pelo workspace do Databricks, opções de compute e as experiências do Lakehouse versus Genie.
• Compreensão e ingestão de dados com o Unity Catalog, incluindo upload de arquivos e o Catalog Explorer.
• Trabalho em Databricks Notebooks e uso do Genie Code para escrever e depurar código.
• Consulta de dados com SQL, gerenciamento de consultas salvas e criação de painéis e visualizações.
• Exploração de dados em linguagem natural com os Genie Agents.
• Uma introdução à IA e machine learning com MLflow e o Data Science Agent.
Ao final do curso, você estará confortável para navegar pelo Databricks, encontrar e governar dados no Unity Catalog, escrever código SQL e em notebook com assistência de IA, criar painéis e explorar dados com o Genie.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31804","entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3425"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3425"}}],"nid":31804,"vid":248573,"title":"Get Started with SQL Analytics and BI on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta o Databricks Data Intelligence Platform e as habilidades essenciais que um analista de dados precisa para o trabalho diário de analítica SQL e BI. Você navegará pelo workspace e pelo Unity Catalog, escreverá consultas SQL em tabelas gerenciadas pelo Unity Catalog a partir de um Serverless SQL Warehouse, usará o Genie Code para gerar e depurar SQL, trabalhará com o Delta Lake (DML, histórico de versões, viagem do tempo e restauração), criará e publicará Painel de AI/BI, e criará Genie Agents para analítica conversacional.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31805","entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3426"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3426"}}],"nid":31805,"vid":248574,"title":"Get Started with SQL Analytics and BI on Databricks - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso apresenta o Databricks Data Intelligence Platform e as habilidades essenciais que um analista de dados precisa para o trabalho diário de analítica SQL e BI. Você navegará pelo workspace e pelo Unity Catalog, escreverá consultas SQL em tabelas gerenciadas pelo Unity Catalog a partir de um Serverless SQL Warehouse, usará o Genie Code para gerar e depurar SQL, trabalhará com o Delta Lake (DML, histórico de versões, viagem do tempo e restauração), criará e publicará Painel de AI/BI, e criará Genie Agents para analítica conversacional.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31048","entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-6061"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-6061"}}],"nid":31048,"vid":246145,"title":"Building Agentic Applications on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso ensina os alunos a criar aplicações agentic de nível de produção no Databricks. Os alunos aprendem a criar agent tools governadas usando Unity Catalog e MCP, criar sistemas single e multi-agent com o OpenAI Agents SDK e aproveitar Agent Bricks e Genie para casos de uso de knowledge assistant orquestrados com um supervisor agent. O curso cobre a progressão completa desde a prototipagem de tools até a implantação em produção, com experiência hands-on usando MLflow tracing para observar a execução do agent.
Observação: Nos arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão “Próxima lição”, pois isso pode impedir que o módulo SCORM seja marcado como concluído.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31049","entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-6062"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-6062"}}],"nid":31049,"vid":246146,"title":"Building Agentic Applications on Databricks - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso ensina os alunos a criar aplicações agentic de nível de produção no Databricks. Os alunos aprendem a criar agent tools governadas usando Unity Catalog e MCP, criar sistemas single e multi-agent com o OpenAI Agents SDK e aproveitar Agent Bricks e Genie para casos de uso de knowledge assistant orquestrados com um supervisor agent. O curso cobre a progressão completa desde a prototipagem de tools até a implantação em produção, com experiência hands-on usando MLflow tracing para observar a execução do agent.
Observação: Nos arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão “Próxima lição”, pois isso pode impedir que o módulo SCORM seja marcado como concluído.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31025","entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-6236"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-6236"}}],"nid":31025,"vid":246057,"title":"SQL Programming and Procedural Logic - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você explorará habilidades essenciais de programação SQL e lógica procedural no Databricks, com foco em como construir fluxos de trabalho analíticos modulares, sustentáveis e prontos para produção. Você começará aprendendo sobre construções SQL fundamentais — como Common Table Expressions (incluindo CTEs recursivas avançadas), objetos com escopo de sessão como visualizações e tabelas temporárias e User Defined Functions — que tornam seu desenvolvimento SQL mais limpo e reutilizável. O curso então o orienta por técnicas avançadas de scripting SQL usando instruções compostas, variáveis, fluxo de controle, condicionais, loops e tratamento robusto de erros para criar processos SQL estruturados e flexíveis. Você também aprenderá como garantir consistência de dados nesses pipelines de várias etapas usando transações de várias instruções compatíveis com ACID. Por fim, você descobrirá como encapsular lógica em SQL Stored Procedures e orquestrar fluxos de trabalho complexos com Lakeflow Jobs e estratégias de migração, transformando tarefas legadas em pipelines modulares e automatizados que aproveitam todos os recursos da plataforma Databricks.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31026","entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-6237"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-6237"}}],"nid":31026,"vid":246058,"title":"SQL Programming and Procedural Logic - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, você explorará habilidades essenciais de programação SQL e lógica procedural no Databricks, com foco em como construir fluxos de trabalho analíticos modulares, sustentáveis e prontos para produção. Você começará aprendendo sobre construções SQL fundamentais — como Common Table Expressions (incluindo CTEs recursivas avançadas), objetos com escopo de sessão como visualizações e tabelas temporárias e User Defined Functions — que tornam seu desenvolvimento SQL mais limpo e reutilizável. O curso então o orienta por técnicas avançadas de scripting SQL usando instruções compostas, variáveis, fluxo de controle, condicionais, loops e tratamento robusto de erros para criar processos SQL estruturados e flexíveis. Você também aprenderá como garantir consistência de dados nesses pipelines de várias etapas usando transações de várias instruções compatíveis com ACID. Por fim, você descobrirá como encapsular lógica em SQL Stored Procedures e orquestrar fluxos de trabalho complexos com Lakeflow Jobs e estratégias de migração, transformando tarefas legadas em pipelines modulares e automatizados que aproveitam todos os recursos da plataforma Databricks.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30895","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6203"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-apps-portuguese-br-6203"}}],"nid":30895,"vid":245355,"title":"Get Started with Databricks Apps - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta o Databricks Apps, um recurso que capacita desenvolvedores a criar e implantar aplicações seguras de dados e IA diretamente na plataforma Databricks. É destinado principalmente a cientistas de dados, engenheiros de dados e desenvolvedores que precisam criar aplicações personalizadas que tornem os insights de dados acessíveis a usuários não técnicos dentro de suas organizações.
O curso oferece uma visão geral dos principais componentes do Databricks Apps, seguida pela implantação de aplicações simples que se integram a um serviço externo, bem como a um recurso do Databricks.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-24T09:00:00"},"endDate":{"value":"2026-11-24T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-16T09:00:00"},"endDate":{"value":"2026-12-16T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T11:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"30848","entityUrl":{"path":"/br/training/catalog/building-rag-agents-with-agent-bricks-portuguese-br-6036"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-rag-agents-with-agent-bricks-portuguese-br-6036"}}],"nid":30848,"vid":244641,"title":"Building RAG Agents with Agent Bricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece treinamento hands-on para criar retrieval agents usando Databricks Agent Bricks. Os participantes aprenderão a explorar e consultar Knowledge Assistants, fazer o parse de documentos não estruturados em dados estruturados usando AI Functions, fazer chunking de texto para retrieval semântico, criar indexes de AI Search e criar Knowledge Assistants prontos para produção com suporte de múltiplas fontes de conhecimento.
Observação: Nos arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão “Próxima lição”, pois isso pode impedir que o módulo SCORM seja marcado como concluído.
Este curso introdutório apresenta o Databricks Lakebase, um serviço PostgreSQL totalmente gerenciado integrado ao Databricks Data Intelligence Platform que aproxima as cargas de trabalho operacionais (OLTP) e analíticas (OLAP).
O curso começa com uma aula conceitual que compara os sistemas OLTP e OLAP, explicando suas diferentes características de desempenho, modelos de armazenamento e casos de uso típicos. Você também irá explorar os desafios que as organizações enfrentam ao manter bancos de dados transacionais e plataformas analíticas separados, incluindo movimentação de dados, latência e complexidade arquitetural.
Em seguida, você aprenderá como o Databricks Lakebase ajuda a enfrentar esses desafios ao fornecer um banco de dados operacional compatível com PostgreSQL que se integra diretamente ao Databricks Lakehouse, permitindo que aplicações operacionais e a analítica trabalhem juntas em uma plataforma unificada.
Por meio de laboratórios práticos, você irá:
Criar e explorar um projeto Lakebase usando compute com escalonamento automático
• Navegar pela interface do Lakebase, incluindo ramificação, monitoramento e configurações
• Criar e executar query em tabelas usando o Lakebase SQL Editor
• Executar query nos dados do Lakebase a partir do Databricks usando Lakehouse Federation e catálogos estrangeiros
• Realizar ETL Reverso sincronizando tabelas Delta com o Lakebase
• Conectar ao Lakebase a partir do Python e realizar operações básicas de CRUD
Este é um curso introdutório, portanto o foco está na compreensão dos conceitos fundamentais e dos fluxos de trabalho básicos para trabalhar com o Lakebase. A construção de aplicações completas de produção sobre o Lakebase está fora do escopo deste curso.
Ao final do curso, você compreenderá como o Lakebase permite que as organizações integrem sistemas operacionais e analítica em uma única plataforma governada, baseada no Unity Catalog e no Databricks Lakehouse.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30757","entityUrl":{"path":"/br/training/catalog/get-started-with-data-governance-on-databricks-portuguese-br-6137"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-data-governance-on-databricks-portuguese-br-6137"}}],"nid":30757,"vid":242127,"title":"Get Started with Data Governance on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você irá explorar o Unity Catalog e os controles de acesso refinados no Databricks com demonstrações práticas e um laboratório final. Você aprenderá sobre tipos de tabela, configuração de catálogo e esquema, gerenciamento de acesso baseado em grupo e estratégias de migração de controles de acesso. O curso inclui demonstrações sobre a aplicação de Controles de Acesso Refinados com Segurança em Nível de Linha e Mascaramento de Colunas, controle de acesso baseado em atributos, combinação de controles, migração de controles e um laboratório para implementação abrangente de governança.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30706","entityUrl":{"path":"/br/training/catalog/get-started-with-ai-agents-on-databricks-portuguese-br-6128"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-ai-agents-on-databricks-portuguese-br-6128"}}],"nid":30706,"vid":241216,"title":"Get Started with AI Agents on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso é uma introdução aos agentes de IA, seu papel nas aplicações modernas de IA e como criar aplicações de agentes de IA na plataforma Databricks. Você aprenderá sobre os princípios dos agentes de IA, como eles diferem dos sistemas de IA tradicionais e explorará seus principais componentes. Por meio de demonstrações interativas e laboratórios práticos, você verá como criar, implantar e avaliar agentes de IA no Databricks usando Databricks AI e Agent Bricks. Ao final deste curso, você compreenderá como criar e implantar agentes de IA usando a Databricks Data + AI Platform.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30699","entityUrl":{"path":"/br/training/catalog/introduction-to-python-for-data-science-and-data-engineering-portuguese-br-6115"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/introduction-to-python-for-data-science-and-data-engineering-portuguese-br-6115"}}],"nid":30699,"vid":241173,"title":"Introduction to Python for Data Science and Data Engineering - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Este curso é destinado a iniciantes completos em Python para fornecer os fundamentos da interação programática com dados. O curso começa com uma introdução básica a expressões de programação, variáveis e tipos de dados. Em seguida, avança para instruções condicionais e de controle, funções, tipos de Coleção, loops, tratamento de erros e classes. Você aprenderá a estender o Python com bibliotecas externas e ganhará experiência usando a biblioteca Pandas para análise e visualização de dados, incluindo o escalonamento de Workflows do Pandas com Apache Spark. Por fim, você irá Explorar os fundamentos da computação em cloud. Ao longo do curso, você obterá prática prática por meio de exercícios de laboratório, com recurso adicionais para aprofundar seu conhecimento de programação após a aula.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30613","entityUrl":{"path":"/br/training/catalog/lakehouse-architecture-fundamentals-portuguese-br-6078"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/lakehouse-architecture-fundamentals-portuguese-br-6078"}}],"nid":30613,"vid":238739,"title":"Lakehouse Architecture Fundamentals - Portuguese BR","price":"0.00","duration":3600,"body":{"processed":"Um curso em nível conceitual baseado em The Data Lakehouse For Dummies. Ele conduz os alunos de \"não tenho certeza do que é um lakehouse\" até serem capazes de manter uma conversa produtiva sobre arquitetura lakehouse e as tecnologias por trás dela: as limitações das arquiteturas legadas, o que é o lakehouse, suas tecnologias principais e como ele viabiliza inteligência de dados e cargas de trabalho unificadas no Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30445","entityUrl":{"path":"/br/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-portuguese-br-6050"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-portuguese-br-6050"}}],"nid":30445,"vid":237602,"title":"Building Semantic Models in Databricks with UC Metric Views - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá como capacitar seus consumidores de dados a obter insights de negócios validados com menos sobrecarga para você e para o restante da equipe de dados e IA da sua empresa. Por meio da construção de uma camada semântica sobre sua camada ouro, você oferecerá aos tomadores de decisão e analistas de negócios a oportunidade de explorar indicadores-chave de desempenho de negócios de maneiras inovadoras, ao mesmo tempo em que mantém operações de dados eficientes e métricas homologadas pela empresa.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-17T14:00:00"},"endDate":{"value":"2026-11-17T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-12T14:00:00"},"endDate":{"value":"2027-01-12T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"30421","entityUrl":{"path":"/br/training/catalog/deploy-workloads-with-lakeflow-jobs-portuguese-br-3278"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/deploy-workloads-with-lakeflow-jobs-portuguese-br-3278"}}],"nid":30421,"vid":237422,"title":"Deploy Workloads with Lakeflow Jobs - Portuguese BR","price":"0.00","duration":14400,"body":{"processed":"O curso Deploy Workloads with Lakeflow Jobs ensina como orquestrar e automatizar fluxos de trabalho de dados, analítica e IA usando Lakeflow Jobs como uma plataforma de orquestração unificada dentro do ecossistema Databricks.
• Você aprenderá a projetar e implementar cargas de trabalho de dados usando Grafos Acíclicos Dirigidos (DAGs), configurar diversas opções de agendamento e implementar recursos avançados de fluxo de trabalho, como execução condicional de tarefas, dependências run-if e loops for each.
• O curso aborda as melhores práticas para criar pipelines robustos e prontos para produção com seleção adequada de compute, orquestração modular, técnicas de tratamento de erros e design tolerante a falhas — tudo nativamente integrado na Databricks Data Intelligence Platform.
Observação: para arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão \"Next Lesson\" (Próxima lição), pois isso pode impedir que o módulo SCORM seja marcado como concluído.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30422","entityUrl":{"path":"/br/training/catalog/deploy-workloads-with-lakeflow-jobs-portuguese-br-3279"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/deploy-workloads-with-lakeflow-jobs-portuguese-br-3279"}}],"nid":30422,"vid":237423,"title":"Deploy Workloads with Lakeflow Jobs - Portuguese BR","price":"75.00","duration":14400,"body":{"processed":"O curso Deploy Workloads with Lakeflow Jobs ensina como orquestrar e automatizar fluxos de trabalho de dados, analítica e IA usando Lakeflow Jobs como uma plataforma de orquestração unificada dentro do ecossistema Databricks.
• Você aprenderá a projetar e implementar cargas de trabalho de dados usando Grafos Acíclicos Dirigidos (DAGs), configurar diversas opções de agendamento e implementar recursos avançados de fluxo de trabalho, como execução condicional de tarefas, dependências run-if e loops for each.
• O curso aborda as melhores práticas para criar pipelines robustos e prontos para produção com seleção adequada de compute, orquestração modular, técnicas de tratamento de erros e design tolerante a falhas — tudo nativamente integrado na Databricks Data Intelligence Platform.
Observação: para arquivos de aula SCORM, feche a janela do SCORM após concluir o conteúdo. Não clique no botão \"Next Lesson\" (Próxima lição), pois isso pode impedir que o módulo SCORM seja marcado como concluído.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30418","entityUrl":{"path":"/br/training/catalog/answering-business-questions-with-databricks-genie-portuguese-br-6023"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/answering-business-questions-with-databricks-genie-portuguese-br-6023"}}],"nid":30418,"vid":237402,"title":"Answering Business Questions with Databricks Genie - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta o Databricks Genie, uma ferramenta de análise conversacional que permite fazer perguntas em linguagem simples sobre os dados da sua organização e obter respostas governadas e seguras. Você aprenderá o que é um Genie Space, como ele mantém seus dados seguros e as práticas recomendadas para obter os melhores resultados. O curso termina com um jogo prático onde você competirá para investigar um mistério de negócios.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30358","entityUrl":{"path":"/br/training/catalog/generative-ai-engineering-with-databricks-portuguese-br-2429"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/generative-ai-engineering-with-databricks-portuguese-br-2429"}}],"nid":30358,"vid":236975,"title":"Generative AI Engineering with Databricks - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Este curso é destinado a cientistas de dados, engenheiros de machine learning e outros profissionais de dados que desejam criar aplicações de IA generativa usando os frameworks mais recentes e populares e os recursos do Databricks.
Observação: a Databricks Academy está migrando para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, deixando de usar apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de laboratório Vocareum.
A seguir, descrevemos cada um dos quatro módulos de quatro horas incluídos neste curso.
Building RAG Agents with Agent Bricks: este curso oferece treinamento prático para criar agentes de recuperação usando o Databricks Agent Bricks. Os participantes aprenderão a explorar e consultar Knowledge Assistants, analisar documentos não estruturados convertendo-os em dados estruturados usando AI Functions, dividir texto em partes (chunks) para recuperação semântica, criar índices de Vector Search e criar Knowledge Assistants prontos para produção com suporte de várias fontes de conhecimento.
Building Agentic Applications on Databricks: este curso ensina os alunos a criar aplicações agênticas de nível de produção no Databricks. Os alunos aprendem a criar ferramentas de agente governadas usando Unity Catalog e MCP, criar sistemas de agente único e multiagente com o OpenAI Agents SDK e aproveitar o Agent Bricks e o Genie para casos de uso de knowledge assistant orquestrados com um agente supervisor. O curso abrange toda a progressão, desde a prototipagem de ferramentas até a implantação em produção, com experiência prática usando o rastreamento (tracing) do MLflow para observar a execução do agente.
Agent Evaluation on Databricks: este curso ensina os alunos a avaliar sistematicamente agentes de IA usando o framework de avaliação do MLflow, abordando os desafios exclusivos dos sistemas de IA não determinísticos com os quais os testes de software tradicionais não conseguem lidar. Os alunos aprendem a implementar várias abordagens de avaliação, incluindo juízes integrados (built-in judges) para critérios comuns, como correção e segurança, juízes baseados em diretrizes para requisitos específicos de negócios e juízes personalizados para necessidades especializadas. O curso abrange tanto a avaliação offline usando conjuntos de dados (datasets) selecionados quanto o monitoramento de produção online, com experiência prática usando os recursos de rastreamento (tracing) do MLflow para entender os padrões de execução do agente e coletar feedback humano de diferentes tipos de partes interessadas. Por meio de demonstrações e laboratórios práticos, os alunos desenvolvem habilidades na criação de fluxos de trabalho de avaliação que impulsionam melhorias contínuas de qualidade ao longo do ciclo de vida de desenvolvimento de agentes de IA.
Deploying and Monitoring Agent Applications on Databricks: este curso aborda o ciclo de vida completo para implantar e monitorar agentes de IA generativa no Databricks. Os participantes aprenderão a implantar agentes como Databricks Apps usando Declarative Automation Bundles (DABs), integrar ferramentas por meio do Model Context Protocol (MCP), instrumentar agentes com o MLflow Tracing e avaliar a qualidade em produção usando scorers, juízes multi-turno e avaliação online. Por meio de demos e laboratórios práticos, os participantes ganharão experiência prática na criação, observação e monitoramento de agentes de IA de nível de produção na plataforma Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30308","entityUrl":{"path":"/br/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-portuguese-br-5971"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-portuguese-br-5971"}}],"nid":30308,"vid":236668,"title":"Deploying and Monitoring Agent Applications on Databricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso cobre o ciclo de vida ponta a ponta para implantar e monitorar agents de generative AI no Databricks. Os participantes aprenderão a implantar agents como Databricks Apps usando Declarative Automation Bundles (DABs), integrar tools via Model Context Protocol (MCP), instrumentar agents com MLflow Tracing e avaliar a qualidade em produção usando scorers, judges multi-turn e avaliação online. Por meio de demos e labs hands-on, os participantes obterão experiência prática criando, observando e monitorando AI agents de nível de produção na plataforma Databricks.
Observação: a Databricks Academy está migrando para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, deixando de usar apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-13T14:00:00"},"endDate":{"value":"2026-10-13T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-10T14:00:00"},"endDate":{"value":"2026-11-10T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-03T09:00:00"},"endDate":{"value":"2026-12-03T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"30310","entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-5982"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-agentic-applications-on-databricks-portuguese-br-5982"}}],"nid":30310,"vid":236670,"title":"Building Agentic Applications on Databricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso ensina os alunos a criar aplicações agentic de nível de produção no Databricks. Os alunos aprendem a criar agent tools governadas usando Unity Catalog e MCP, criar sistemas single e multi-agent com o OpenAI Agents SDK e aproveitar Agent Bricks e Genie para casos de uso de knowledge assistant orquestrados com um supervisor agent. O curso cobre a progressão completa desde a prototipagem de tools até a implantação em produção, com experiência hands-on usando MLflow tracing para observar a execução do agent.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-04T09:00:00"},"endDate":{"value":"2026-11-04T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-01T14:00:00"},"endDate":{"value":"2026-12-01T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-26T09:00:00"},"endDate":{"value":"2027-01-26T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"30294","entityUrl":{"path":"/br/training/catalog/building-rag-agents-with-agent-bricks-portuguese-br-5952"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-rag-agents-with-agent-bricks-portuguese-br-5952"}}],"nid":30294,"vid":236604,"title":"Building RAG Agents with Agent Bricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso oferece treinamento hands-on para criar retrieval agents usando Databricks Agent Bricks. Os participantes aprenderão a explorar e consultar Knowledge Assistants, fazer o parse de documentos não estruturados em dados estruturados usando AI Functions, fazer chunking de texto para retrieval semântico, criar indexes de AI Search e criar Knowledge Assistants prontos para produção com suporte de múltiplas fontes de conhecimento.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-21T09:00:00"},"endDate":{"value":"2026-10-21T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-13T14:00:00"},"endDate":{"value":"2027-01-13T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29826","entityUrl":{"path":"/br/training/catalog/aibi-for-data-analysts-portuguese-br-4195"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/aibi-for-data-analysts-portuguese-br-4195"}}],"nid":29826,"vid":234901,"title":"AI/BI for Data Analysts - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso ensina os analistas de dados a projetar, criar, publicar e operar AI/BI Dashboards no Databricks. Os AI/BI Dashboards combinam dados governados pelo Unity Catalog com visualizações interativas, filtros e integração com o Genie, para que os usuários de negócios possam explorar respostas sem escrever código.
O curso segue uma única construção de ponta a ponta. Você começa com tabelas de origem no Unity Catalog e termina com um dashboard de várias páginas publicado e monitorado. Ao longo do caminho, você aprende como os dashboards se encaixam na família mais ampla de produtos AI/BI do Databricks e onde o Genie, os conjuntos de dados, as visualizações e os filtros se encaixam no fluxo de trabalho.
O conteúdo aborda:
• Os fundamentos dos AI/BI Dashboards e como eles se relacionam com o Genie e com o restante da plataforma Databricks.
• A exploração de dados de origem no Unity Catalog e o design de conjuntos de dados reutilizáveis para dashboards com SQL.
• A criação de visualizações (KPIs, tendências, detalhamentos) e a organização de um dashboard de várias páginas bem estruturado.
• O uso do Genie Code para esboçar SQL, gráficos e filtros a partir de prompts em linguagem natural.
• A adição de filtros para tornar os dashboards interativos e responsivos às perguntas de quem os visualiza.
• A publicação, o compartilhamento e o gerenciamento de permissões para que as pessoas certas possam visualizar e editar o dashboard.
• A execução do dashboard em produção com atualização agendada, cache e monitoramento de uso.
Ao final do curso, você será capaz de partir de uma pergunta de negócio, projetar os conjuntos de dados de apoio, criar um dashboard refinado e entregá-lo ao seu público com as permissões corretas e uma estratégia de atualização que o mantenha preciso.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
Este curso ensina os analistas de dados a projetar, criar, publicar e operar AI/BI Dashboards no Databricks. Os AI/BI Dashboards combinam dados governados pelo Unity Catalog com visualizações interativas, filtros e integração com o Genie, para que os usuários de negócios possam explorar respostas sem escrever código.
O curso segue uma única construção de ponta a ponta. Você começa com tabelas de origem no Unity Catalog e termina com um dashboard de várias páginas publicado e monitorado. Ao longo do caminho, você aprende como os dashboards se encaixam na família mais ampla de produtos AI/BI do Databricks e onde o Genie, os conjuntos de dados, as visualizações e os filtros se encaixam no fluxo de trabalho.
O conteúdo aborda:
• Os fundamentos dos AI/BI Dashboards e como eles se relacionam com o Genie e com o restante da plataforma Databricks.
• A exploração de dados de origem no Unity Catalog e o design de conjuntos de dados reutilizáveis para dashboards com SQL.
• A criação de visualizações (KPIs, tendências, detalhamentos) e a organização de um dashboard de várias páginas bem estruturado.
• O uso do Genie Code para esboçar SQL, gráficos e filtros a partir de prompts em linguagem natural.
• A adição de filtros para tornar os dashboards interativos e responsivos às perguntas de quem os visualiza.
• A publicação, o compartilhamento e o gerenciamento de permissões para que as pessoas certas possam visualizar e editar o dashboard.
• A execução do dashboard em produção com atualização agendada, cache e monitoramento de uso.
Ao final do curso, você será capaz de partir de uma pergunta de negócio, projetar os conjuntos de dados de apoio, criar um dashboard refinado e entregá-lo ao seu público com as permissões corretas e uma estratégia de atualização que o mantenha preciso.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29795","entityUrl":{"path":"/br/training/catalog/catalog-management-and-data-organization-portuguese-br-5920"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/catalog-management-and-data-organization-portuguese-br-5920"}}],"nid":29795,"vid":234755,"title":"Catalog Management and Data Organization - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá como projetar, implementar e governar estruturas de catálogo e organização de dados em larga escala na Plataforma de Inteligência de Dados Databricks. Ele oferece uma visão abrangente do Unity Catalog como a camada de governança centralizada para um lakehouse empresarial. Dividido em cinco módulos, começa posicionando o Unity Catalog dentro do modelo de implantação em nuvem — cobrindo o Account Console, criação de metastore e a hierarquia de funções de administrador. Você então traduzirá topologia organizacional (unidades de negócios, regiões e ambientes dev/QA/prod) em um design escalável de catálogo e schema usando convenções de nomenclatura, padrões de propriedade e delegação MANAGE. O curso então cobre integração segura de armazenamento com credenciais de armazenamento, localizações externas, a hierarquia de armazenamento gerenciado, tabelas gerenciadas versus externas e UC Volumes para dados não-tabulares. Em seguida, você aplicará padrões de acesso e estratégias de isolamento — a cadeia GRANT de três níveis, vinculação workspace-catalog e políticas de Controle de Acesso Baseado em Atributos (ABAC) em nível de schema — para impor proteção de dados refinada em escala. Finalmente, o curso fecha com práticas recomendadas para design de catálogo, automação, permissões de menor privilégio e gerenciamento de acesso baseado em grupo.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-25T09:00:00"},"endDate":{"value":"2026-11-25T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-13T09:00:00"},"endDate":{"value":"2027-01-13T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29790","entityUrl":{"path":"/br/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-portuguese-br-5905"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-portuguese-br-5905"}}],"nid":29790,"vid":234737,"title":"Business Impact Accelerator: Answering Business Questions with Genie - Portuguese BR","price":"0.00","duration":10800,"body":{"processed":"Este curso apresenta o Databricks Genie One, um ambiente de trabalho colaborativo baseado em IA, projetado em torno das suas necessidades e do seu trabalho, onde você pode fazer perguntas em linguagem natural sobre os dados da sua organização e obter respostas seguras e governadas, programar relatórios para execução automática e automatizar seu fluxo de trabalho para realizar mais tarefas com maior rapidez e precisão, pois é baseado nos seus dados e negócios. Você aprenderá o que são Genie, Genie One e Genie Agents, como todos eles mantêm seus dados seguros e as melhores práticas para obter os melhores resultados.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29784","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-3472"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-3472"}}],"nid":29784,"vid":234634,"title":"Get Started with Databricks for Data Engineering - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta as habilidades fundamentais necessárias para executar um fluxo de trabalho básico de engenharia de dados na Databricks Data Intelligence Platform. Você vai explorar o workspace, trabalhar com o Unity Catalog e aprender os blocos de construção que um engenheiro de dados usa no dia a dia no Databricks.
O curso segue um caminho prático. Você começa se familiarizando com o workspace e, em seguida, avança por notebooks de Demo e Lab em pares para cada tópico. As Demos apresentam um conceito com o instrutor ou por meio de um notebook guiado; os Labs pedem que você aplique por conta própria o que acabou de ver.
O conteúdo aborda:
• A Databricks Data Intelligence Platform e como o workspace do Databricks, o Unity Catalog e os notebooks se integram.
• Criação e gerenciamento de tabelas Delta Lake.
• Modificação de dados com INSERT, UPDATE e DELETE.
• Exploração do histórico de versões e do time travel em tabelas Delta.
• Ingestão de dados com as opções do Lakeflow Connect: CTAS, a interface de Upload e COPY INTO.
• Construção de um pipeline de Arquitetura Medallion que transforma dados pelas camadas Bronze, Silver e Gold.
• Automação de pipelines com o Lakeflow Jobs.
• (Bônus) Construção de um pipeline declarativo com o Spark Declarative Pipelines.
Ao final do curso, você se sentirá à vontade para criar tabelas Delta Lake, ingerir dados nelas, transformar esses dados por meio de um pipeline Medallion e automatizar todo o processo como um job agendado.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29785","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-3473"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-3473"}}],"nid":29785,"vid":234635,"title":"Get Started with Databricks for Data Engineering - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso apresenta as habilidades fundamentais necessárias para executar um fluxo de trabalho básico de engenharia de dados na Databricks Data Intelligence Platform. Você vai explorar o workspace, trabalhar com o Unity Catalog e aprender os blocos de construção que um engenheiro de dados usa no dia a dia no Databricks.
O curso segue um caminho prático. Você começa se familiarizando com o workspace e, em seguida, avança por notebooks de Demo e Lab em pares para cada tópico. As Demos apresentam um conceito com o instrutor ou por meio de um notebook guiado; os Labs pedem que você aplique por conta própria o que acabou de ver.
O conteúdo aborda:
• A Databricks Data Intelligence Platform e como o workspace do Databricks, o Unity Catalog e os notebooks se integram.
• Criação e gerenciamento de tabelas Delta Lake.
• Modificação de dados com INSERT, UPDATE e DELETE.
• Exploração do histórico de versões e do time travel em tabelas Delta.
• Ingestão de dados com as opções do Lakeflow Connect: CTAS, a interface de Upload e COPY INTO.
• Construção de um pipeline de Arquitetura Medallion que transforma dados pelas camadas Bronze, Silver e Gold.
• Automação de pipelines com o Lakeflow Jobs.
• (Bônus) Construção de um pipeline declarativo com o Spark Declarative Pipelines.
Ao final do curso, você se sentirá à vontade para criar tabelas Delta Lake, ingerir dados nelas, transformar esses dados por meio de um pipeline Medallion e automatizar todo o processo como um job agendado.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29756","entityUrl":{"path":"/br/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-portuguese-br-3738"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-portuguese-br-3738"}}],"nid":29756,"vid":234458,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI) - Portuguese BR","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
Este curso apresenta as habilidades fundamentais necessárias para executar um fluxo de trabalho básico de engenharia de dados na Databricks Data Intelligence Platform. Você vai explorar o workspace, trabalhar com o Unity Catalog e aprender os blocos de construção que um engenheiro de dados usa no dia a dia no Databricks.
O curso segue um caminho prático. Você começa se familiarizando com o workspace e, em seguida, avança por notebooks de Demo e Lab em pares para cada tópico. As Demos apresentam um conceito com o instrutor ou por meio de um notebook guiado; os Labs pedem que você aplique por conta própria o que acabou de ver.
Get Started with SQL Analytics and BI on Databricks
Este curso apresenta o Databricks Data Intelligence Platform, abordando habilidades essenciais para análise de dados e armazenamento. Aprenda a navegar pelo workspace, trabalhar com objetos de dados, executar SQL queries, usar recursos Delta Lake e criar dashboards. Os laboratórios práticos proporcionam experiência prática em um ambiente Databricks ao vivo.
Pode criar uma Databricks Free Edition account e experimentar as demonstrações passo a passo num ambiente prático.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-27T09:00:00"},"endDate":{"value":"2026-10-27T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-24T09:00:00"},"endDate":{"value":"2026-11-24T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-26T09:00:00"},"endDate":{"value":"2027-01-26T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29615","entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-5826"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-programming-and-procedural-logic-portuguese-br-5826"}}],"nid":29615,"vid":234121,"title":"SQL Programming and Procedural Logic - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você explorará habilidades essenciais de programação SQL e lógica procedural no Databricks, com foco em como construir fluxos de trabalho analíticos modulares, sustentáveis e prontos para produção. Você começará aprendendo sobre construções SQL fundamentais — como Common Table Expressions (incluindo CTEs recursivas avançadas), objetos com escopo de sessão como visualizações e tabelas temporárias e User Defined Functions — que tornam seu desenvolvimento SQL mais limpo e reutilizável. O curso então o orienta por técnicas avançadas de scripting SQL usando instruções compostas, variáveis, fluxo de controle, condicionais, loops e tratamento robusto de erros para criar processos SQL estruturados e flexíveis. Você também aprenderá como garantir consistência de dados nesses pipelines de várias etapas usando transações de várias instruções compatíveis com ACID. Por fim, você descobrirá como encapsular lógica em SQL Stored Procedures e orquestrar fluxos de trabalho complexos com Lakeflow Jobs e estratégias de migração, transformando tarefas legadas em pipelines modulares e automatizados que aproveitam todos os recursos da plataforma Databricks.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-26T14:00:00"},"endDate":{"value":"2026-11-26T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-07T14:00:00"},"endDate":{"value":"2027-01-07T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29618","entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-5830"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-5830"}}],"nid":29618,"vid":234124,"title":"Machine Learning Model Development - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso abrangente fornece um guia prático para o desenvolvimento de modelos tradicionais de aprendizado de máquina no Databricks, enfatizando demonstrações práticas e fluxos de trabalho usando bibliotecas de ML populares. Os participantes explorarão as principais técnicas de ML, incluindo regressão e clustering, enquanto aproveitam os poderosos recursos do Databricks. O curso aborda a integração do MLflow para rastreamento de modelos, a Databricks Feature Store para gerenciamento de recursos e o Optuna para ajuste de hiperparâmetros. Além disso, os participantes aprenderão como acelerar o desenvolvimento de modelos com o Genie Code, o assistente de codificação baseado em IA da Databricks que usa linguagem natural, conexões MCP, instruções e habilidades para orientar todo o ciclo de vida de ML. Ao final do curso, os alunos terão habilidades práticas do mundo real para desenvolver, otimizar e implantar modelos de aprendizado de máquina de forma eficiente no ambiente Databricks.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29619","entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-5831"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-5831"}}],"nid":29619,"vid":234125,"title":"Machine Learning Model Development - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso abrangente fornece um guia prático para o desenvolvimento de modelos tradicionais de aprendizado de máquina no Databricks, enfatizando demonstrações práticas e fluxos de trabalho usando bibliotecas de ML populares. Os participantes explorarão as principais técnicas de ML, incluindo regressão e clustering, enquanto aproveitam os poderosos recursos do Databricks. O curso aborda a integração do MLflow para rastreamento de modelos, a Databricks Feature Store para gerenciamento de recursos e o Optuna para ajuste de hiperparâmetros. Além disso, os participantes aprenderão como acelerar o desenvolvimento de modelos com o Genie Code, o assistente de codificação baseado em IA da Databricks que usa linguagem natural, conexões MCP, instruções e habilidades para orientar todo o ciclo de vida de ML. Ao final do curso, os alunos terão habilidades práticas do mundo real para desenvolver, otimizar e implantar modelos de aprendizado de máquina de forma eficiente no ambiente Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29450","entityUrl":{"path":"/br/training/catalog/building-reliable-conversational-agents-with-genie-portuguese-br-5797"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-reliable-conversational-agents-with-genie-portuguese-br-5797"}}],"nid":29450,"vid":232897,"title":"Building Reliable Conversational Agents with Genie - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso ensina como projetar, construir e manter um Genie Space do Databricks, uma interface de linguagem natural que permite que usuários de negócios façam perguntas sobre dados controlados e recebam respostas baseadas em SQL sem precisar escrever código.
Você aprenderá como o Genie se encaixa na família de produtos de IA/BI do Databricks e como ele traduz a linguagem natural em consultas SQL confiáveis. O curso se concentra no que é necessário para criar um Genie Space que forneça resultados precisos, consistentes e confiáveis.
Você seguirá um fluxo de trabalho completo, do início ao fim, desde a compreensão dos dados de origem e a definição de parâmetros de referência até a configuração e o aprimoramento de um Genie Space usando o conjunto completo de ferramentas de curadoria do Knowledge Store. Isso inclui metadados, sinônimos, correspondência de prompts, lógica SQL, consultas de exemplo e instruções de texto.
Você também aprenderá a compartilhar Genie Spaces com usuários de negócios por meio do Databricks One, compreenderá como a governança do Unity Catalog é aplicada automaticamente e utilizará o monitoramento e o feedback dos usuários para melhorar continuamente a qualidade ao longo do tempo.
Ao final do curso, você será capaz de criar e gerenciar um Genie Space pronto para produção que ofereça análises conversacionais em escala, governadas e no modelo de autoatendimento.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-25T14:00:00"},"endDate":{"value":"2026-11-25T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-06T14:00:00"},"endDate":{"value":"2027-01-06T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29383","entityUrl":{"path":"/br/training/catalog/lakebase-app-integration-and-management-portuguese-br-5691"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/lakebase-app-integration-and-management-portuguese-br-5691"}}],"nid":29383,"vid":231428,"title":"Lakebase App Integration and Management - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá a integrar o Databricks Apps ao Lakebase, a plataforma PostgreSQL totalmente gerenciada e nativa cloud do Databricks, para criar fluxos de trabalho de aplicativos seguros e prontos para uso empresarial. Com base no conhecimento fundamental sobre o Databricks Apps e o Lakebase, este curso foca nos fundamentos do PostgreSQL, no Lakebase Autoscaling, em práticas seguras de SQL, no gerenciamento seguro de conexões, no acesso baseado em funções, na integração da Data API e no desenvolvimento baseado em branches. Você também explorará como o AppKit pode acelerar o desenvolvimento de aplicativos dentro desse fluxo de trabalho, ajudando você a passar dos conceitos de integração para a implementação de forma mais eficiente.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-18T09:00:00"},"endDate":{"value":"2026-11-18T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-06T09:00:00"},"endDate":{"value":"2027-01-06T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29359","entityUrl":{"path":"/br/training/catalog/building-enterprise-applications-with-databricks-apps-portuguese-br-5629"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-enterprise-applications-with-databricks-apps-portuguese-br-5629"}}],"nid":29359,"vid":230950,"title":"Building Enterprise Applications with Databricks Apps - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso apresenta o Databricks Apps, um novo recurso que permite que os desenvolvedores criem e implantem aplicações seguras de dados e IA diretamente na plataforma Databricks. Ele foi pensado principalmente para cientistas de dados, engenheiros de dados e desenvolvedores que precisam criar aplicações personalizadas que tornem os insights de dados acessíveis a usuários não técnicos dentro de suas organizações.
O curso começa com uma visão geral dos principais componentes do Databricks Apps, seguida da implantação de um aplicativo simples que se integra a um serviço externo. Em seguida, você aprenderá a criar e implantar aplicações inteligentes e data-driven que se integram aos recursos da plataforma Databricks. O curso aborda, então, como desenvolver aplicativos fora do ambiente Databricks. Ele se encerra com um tratamento detalhado das melhores práticas para implementar aplicações corporativas seguras e confiáveis.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-24T14:00:00"},"endDate":{"value":"2026-11-24T18:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-05T14:00:00"},"endDate":{"value":"2027-01-05T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"29196","entityUrl":{"path":"/br/training/catalog/get-started-with-lakebase-portuguese-br-5452"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-lakebase-portuguese-br-5452"}}],"nid":29196,"vid":229230,"title":"Get Started with Lakebase - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso introdutório apresenta o Databricks Lakebase, um serviço PostgreSQL totalmente gerenciado integrado ao Databricks Data Intelligence Platform que aproxima as cargas de trabalho operacionais (OLTP) e analíticas (OLAP).
O curso começa com uma aula conceitual que compara os sistemas OLTP e OLAP, explicando suas diferentes características de desempenho, modelos de armazenamento e casos de uso típicos. Você também irá explorar os desafios que as organizações enfrentam ao manter bancos de dados transacionais e plataformas analíticas separados, incluindo movimentação de dados, latência e complexidade arquitetural.
Em seguida, você aprenderá como o Databricks Lakebase ajuda a enfrentar esses desafios ao fornecer um banco de dados operacional compatível com PostgreSQL que se integra diretamente ao Databricks Lakehouse, permitindo que aplicações operacionais e a analítica trabalhem juntas em uma plataforma unificada.
Por meio de laboratórios práticos, você irá:
Criar e explorar um projeto Lakebase usando compute com escalonamento automático
• Navegar pela interface do Lakebase, incluindo ramificação, monitoramento e configurações
• Criar e executar query em tabelas usando o Lakebase SQL Editor
• Executar query nos dados do Lakebase a partir do Databricks usando Lakehouse Federation e catálogos estrangeiros
• Realizar ETL Reverso sincronizando tabelas Delta com o Lakebase
• Conectar ao Lakebase a partir do Python e realizar operações básicas de CRUD
Este é um curso introdutório, portanto o foco está na compreensão dos conceitos fundamentais e dos fluxos de trabalho básicos para trabalhar com o Lakebase. A construção de aplicações completas de produção sobre o Lakebase está fora do escopo deste curso.
Ao final do curso, você compreenderá como o Lakebase permite que as organizações integrem sistemas operacionais e analítica em uma única plataforma governada, baseada no Unity Catalog e no Databricks Lakehouse.
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29076","entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5508"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5508"}}],"nid":29076,"vid":228190,"title":"Building ETL Pipelines with SQL - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso ensina como criar ETL pipelines prontos para produção usando SQL puro na Databricks Data Intelligence Platform. Os alunos aprendem Streaming Tables com Auto Loader para ingestão incremental, Materialized Views com atualização incremental para transformações Prata para Ouro, AUTO CDC (FLOW AUTO CDC) para gerenciamento declarativo de dimensões SCD Tipo 1 e Tipo 2, e Lakeflow Jobs com tarefas de arquivo SQL para orquestração em produção. O curso segue um dataset de varejo realista através da arquitetura medalhão (Bronze → Prata → Ouro).
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29077","entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5513"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5513"}}],"nid":29077,"vid":228191,"title":"Building ETL Pipelines with SQL - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso ensina como criar ETL pipelines prontos para produção usando SQL puro na Databricks Data Intelligence Platform. Os alunos aprendem Streaming Tables com Auto Loader para ingestão incremental, Materialized Views com atualização incremental para transformações Prata para Ouro, AUTO CDC (FLOW AUTO CDC) para gerenciamento declarativo de dimensões SCD Tipo 1 e Tipo 2, e Lakeflow Jobs com tarefas de arquivo SQL para orquestração em produção. O curso segue um dataset de varejo realista através da arquitetura medalhão (Bronze → Prata → Ouro).
Observação: Para os ficheiros das aulas SCORM, por favor certifique-se de fechar a janela SCORM após concluir o conteúdo. Não clique no botão 'Next Lesson', pois isso pode impedir que o módulo SCORM seja marcado como completo.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29025","entityUrl":{"path":"/br/training/catalog/architecting-data-warehouses-for-large-scale-deployments-portuguese-br-5498"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/architecting-data-warehouses-for-large-scale-deployments-portuguese-br-5498"}}],"nid":29025,"vid":227787,"title":"Architecting Data Warehouses for Large-Scale Deployments - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso aborda a otimização de desempenho, o controle de custos e a segurança para implantações de data warehousing em grande escala.
Este curso é destinado a profissionais de data warehousing responsáveis por gerenciar ambientes Databricks que atendem centenas ou milhares de usuários em várias unidades de negócio. Você adquirirá as habilidades necessárias para escalar com eficiência as operações de data warehousing, mantendo alto desempenho, custo-benefício e conformidade com os padrões de segurança.
Observação: A Databricks Academy está a migrar para um formato baseado em notebooks para as aulas dentro do ambiente Databricks, descontinuando o uso de diapositivos nas aulas. Pode aceder aos notebooks das aulas no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-20T09:00:00"},"endDate":{"value":"2026-10-20T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-02T09:00:00"},"endDate":{"value":"2026-12-02T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-26T14:00:00"},"endDate":{"value":"2027-01-26T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28965","entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5475"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/building-etl-pipelines-with-sql-portuguese-br-5475"}}],"nid":28965,"vid":226681,"title":"Building ETL Pipelines with SQL - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso ensina como construir pipelines ETL prontos para produção usando SQL puro na Databricks Data Intelligence Platform. Os alunos aprendem sobre Streaming Tables com Auto Loader para ingestão incremental, Materialized Views com refresh incremental para transformações de Prata para ouro, AUTO CDC (FLOW AUTO CDC) para gerenciamento declarativo de dimensões SCD Tipo 1 e Tipo 2, e Apache Spark Declarative Pipelines (SDP) para agrupar esses objetos em pipelines multi-tabela de produção com expectativas de qualidade de dados, tabelas PRIVATE e monitoramento unificado. O curso acompanha um dataset de varejo realista por meio da Arquitetura Medallion (Bronze → Prata → Ouro). A orquestração com LakeFlow Jobs está disponível como módulo bônus.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-10-15T09:00:00"},"endDate":{"value":"2026-10-15T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-19T09:00:00"},"endDate":{"value":"2026-11-19T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-08T14:00:00"},"endDate":{"value":"2026-12-08T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28640","entityUrl":{"path":"/br/training/catalog/get-started-with-lakebase-portuguese-br-5400"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-lakebase-portuguese-br-5400"}}],"nid":28640,"vid":220805,"title":"Get Started with Lakebase - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso introdutório apresenta o Databricks Lakebase, um serviço PostgreSQL totalmente gerenciado integrado ao Databricks Data Intelligence Platform que aproxima as cargas de trabalho operacionais (OLTP) e analíticas (OLAP).
O curso começa com uma aula conceitual que compara os sistemas OLTP e OLAP, explicando suas diferentes características de desempenho, modelos de armazenamento e casos de uso típicos. Você também irá explorar os desafios que as organizações enfrentam ao manter bancos de dados transacionais e plataformas analíticas separados, incluindo movimentação de dados, latência e complexidade arquitetural.
Em seguida, você aprenderá como o Databricks Lakebase ajuda a enfrentar esses desafios ao fornecer um banco de dados operacional compatível com PostgreSQL que se integra diretamente ao Databricks Lakehouse, permitindo que aplicações operacionais e a analítica trabalhem juntas em uma plataforma unificada.
Este é um curso introdutório, portanto o foco está na compreensão dos conceitos fundamentais e dos fluxos de trabalho básicos para trabalhar com o Lakebase. A construção de aplicações completas de produção sobre o Lakebase está fora do escopo deste curso.
Ao final do curso, você compreenderá como o Lakebase permite que as organizações integrem sistemas operacionais e analítica em uma única plataforma governada, baseada no Unity Catalog e no Databricks Lakehouse.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28531","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4630"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4630"}}],"nid":28531,"vid":218905,"title":"Get Started with Databricks Platform Administration - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, você aprenderá os conceitos básicos de administração de plataforma no Databricks Data Intelligence Platform. Ele oferece uma visão geral abrangante do Unity Catalog, um componente vital para uma governança de dados eficaz em ambientes Databricks. Dividido em cinco módulos, ele começa com uma introdução detalhada à infraestrutura Databricks e sua data intelligence platform, incluindo um passo a passo detalhado do Databricks Workspace. Você explorará os princípios de governança de dados dentro do Unity Catalog, abordando seus principais conceitos, arquitetura e funções. O curso enfatiza ainda o gerenciamento de metastores Unity Catalog e recursos de compute, incluindo clusters e warehouses SQL. Por fim, você dominará o controle de acesso a dados aprendendo sobre privilégios, acesso refinado e como controlar objetos de dados. Ao final, você estará equipado com habilidades essenciais para administrar o Unity Catalog para implementar uma governança de dados eficaz, otimizar recursos de compute e aplicar estratégias robustas de segurança de dados. Com a compra de uma assinatura Databricks Labs, o curso também se encerra com um exercício de laboratório abrangente para praticar o que você aprendeu em um ambiente Databricks Workspace ao vivo.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28070","entityUrl":{"path":"/br/training/catalog/automated-deployment-with-databricks-asset-bundles-portuguese-br-3998"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/automated-deployment-with-databricks-asset-bundles-portuguese-br-3998"}}],"nid":28070,"vid":217375,"title":"Automated Deployment with Databricks Asset Bundles - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso oferece uma revisão abrangente dos princípios de DevOps e sua aplicação em projetos Databricks. Ele começa com uma visão geral dos principais conceitos de DevOps, DataOps, continuous integration (CI), continuous deployment (CD) e testes, e explora como esses princípios podem ser aplicados a pipelines de engenharia de dados.
Em seguida, o curso se concentra na continuous deployment dentro do processo de CI/CD, examinando ferramentas como a Databricks REST API, o SDK e a CLI para a implantação de projetos. Você aprenderá sobre os Databricks Asset Bundles (DABs) e como eles se encaixam no processo de CI/CD. Você se aprofundará em seus principais componentes, estrutura de pastas e como eles otimizam a implantação em vários ambientes de destino na Databricks. Você também aprenderá como adicionar variáveis, modificar, validar, implantar e executar Databricks Asset Bundles para vários ambientes com diferentes configurações usando a Databricks CLI.
Por fim, o curso apresenta o Visual Studio Code como um Interactive Development Environment (IDE) para criar, testar e implantar Databricks Asset Bundles localmente, otimizando seu processo de desenvolvimento. O curso conclui com uma introdução à automação de pipelines de implantação usando o GitHub Actions para aprimorar o fluxo de trabalho de CI/CD com Databricks Asset Bundles.
Ao final deste curso, você estará apto a automatizar implantações de projetos Databricks com Databricks Asset Bundles, melhorando a eficiência por meio de práticas de DevOps.
Nota: Este curso é o quarto da série “Engenharia de dados avançada com Databricks”.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28260","entityUrl":{"path":"/br/training/catalog/machine-learning-operations-portuguese-br-2596"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-operations-portuguese-br-2596"}}],"nid":28260,"vid":217565,"title":"Machine Learning Operations - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso irá guiar os participantes por uma exploração abrangente das operações de modelo do machine learning, com foco em MLOps e gerenciamento do ciclo de vida do modelo. O segmento inicial aborda os componentes essenciais de MLOps e as melhores práticas, fornecendo aos participantes uma base sólida para operacionalizar modelos do machine learning de forma eficaz. Na parte final do curso, aprofundaremos os conceitos básicos do ciclo de vida do modelo, demonstrando como navegá-lo de forma fluida utilizando o Model Registry em conjunto com o Unity Catalog para um gerenciamento eficiente de modelos. Ao término do curso, os participantes terão adquirido insights práticos e uma compreensão abrangente dos princípios de MLOps, equipados com as habilidades necessárias para navegar pelo intrincado cenário das operações de modelo do machine learning.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-11T14:00:00"},"endDate":{"value":"2026-11-11T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28345","entityUrl":{"path":"/br/training/catalog/data-ingestion-with-delta-lake-portuguese-br-3302"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-ingestion-with-delta-lake-portuguese-br-3302"}}],"nid":28345,"vid":217650,"title":"Data Ingestion with Delta Lake - Portuguese BR","price":"75.00","duration":14400,"body":{"processed":"Este curso prepara profissionais de dados para utilizar a plataforma de inteligência do Databricks e produzir pipelines de ETL. Os alunos usarão Delta Live Tables com Spark SQL e Python para definir e programar pipelines que processam incrementalmente novos dados de uma variedade de fontes de dados no Lakehouse. Os alunos também orquestrarão tarefas com Databricks Workflows e promoverão código com Databricks Repos.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28074","entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-4012"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-4012"}}],"nid":28074,"vid":217379,"title":"Databricks Data Privacy - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este conteúdo oferece um guia completo para a gestão da privacidade de dados no Databricks. Aborda temas essenciais como a arquitetura do Delta Lake, o isolamento regional de dados, a compliance com o RGPD/CCPA e a utilização do Change Data Feed (CDF). Através de demonstrações práticas e laboratórios interativos, os participantes aprendem a utilizar as funcionalidades do Unity Catalog para proteger dados confidenciais e garantir a compliance, capacitando-os para salvaguardar a integridade dos dados de forma eficaz.
Nota: Este curso é o segundo da série “Engenharia de dados avançada com Databricks”.
Languages Available: English | 日本語 | Português BR
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28261","entityUrl":{"path":"/br/training/catalog/data-preparation-for-machine-learning-portuguese-br-2598"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-preparation-for-machine-learning-portuguese-br-2598"}}],"nid":28261,"vid":217566,"title":"Data Preparation for Machine Learning - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso se concentra nos fundamentos da preparação de dados para machine learning usando o Databricks. Os participantes aprenderão habilidades essenciais para explorar, limpar e organizar dados voltados para aplicações tradicionais de machine learning. Os principais tópicos incluem visualização de dados, Engenharia de Recursos e estratégias ideais de armazenamento de recursos. Por meio de exercícios práticos, os participantes adquirirão experiência prática na preparação eficiente de conjuntos de dados para machine learning no Databricks. Este curso foi desenvolvido para cientistas de dados de nível associado e profissionais de machine learning, bem como para indivíduos que buscam aprimorar sua proficiência na preparação de dados, garantindo uma base sólida para a implantação com Êxito de modelo do machine learning.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-05T09:00:00"},"endDate":{"value":"2026-11-05T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28353","entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-3372"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-3372"}}],"nid":28353,"vid":217658,"title":"Databricks Performance Optimization - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, aprenderá como otimizar as cargas de trabalho e o layout físico com o Spark e o Delta Lake, bem como analisar a interface do utilizador do Spark para avaliar o desempenho e depurar aplicações. Abordaremos temas como transmissão, net clustering, data skipping, cache, photons e muito mais.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28075","entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-4013"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-4013"}}],"nid":28075,"vid":217380,"title":"Databricks Data Privacy - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este conteúdo oferece um guia completo para a gestão da privacidade de dados no Databricks. Aborda temas essenciais como a arquitetura do Delta Lake, o isolamento regional de dados, a compliance com o RGPD/CCPA e a utilização do Change Data Feed (CDF). Através de demonstrações práticas e laboratórios interativos, os participantes aprendem a utilizar as funcionalidades do Unity Catalog para proteger dados confidenciais e garantir a compliance, capacitando-os para salvaguardar a integridade dos dados de forma eficaz.
Nota: Este curso é o segundo da série “Engenharia de dados avançada com Databricks”.
Languages Available: English | 日本語 | Português BR
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28262","entityUrl":{"path":"/br/training/catalog/machine-learning-with-databricks-portuguese-br-2600"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-with-databricks-portuguese-br-2600"}}],"nid":28262,"vid":217567,"title":"Machine Learning with Databricks - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Bem-vindo ao Machine Learning com Databricks!
Este curso é a sua porta de entrada para dominar os machine learning workflows em Databricks. Mergulhe na preparação de dados, desenvolvimento de modelos, implementação e operações, orientado por instrutores especializados. Aprenda competências essenciais para exploração de dados, treino de modelos e estratégias de implementação adaptadas para Databricks. No final do curso, terá o conhecimento e a confiança para navegar por todo o ciclo de vida do machine learning na plataforma Databricks, capacitando-o a construir e implementar soluções robustas de machine learning de forma eficiente.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Preparação de Dados para Machine Learning
Este curso se concentra nos fundamentos da preparação de dados para machine learning usando o Databricks. Os participantes aprenderão habilidades essenciais para explorar, limpar e organizar dados voltados para aplicações tradicionais de machine learning. Os principais tópicos incluem visualização de dados, Engenharia de Recursos e estratégias ideais de armazenamento de recursos. Por meio de exercícios práticos, os participantes adquirirão experiência prática na preparação eficiente de conjuntos de dados para machine learning no Databricks. Este curso foi desenvolvido para cientistas de dados de nível associado e profissionais de machine learning, bem como para indivíduos que buscam aprimorar sua proficiência na preparação de dados, garantindo uma base sólida para a implantação com Êxito de modelo do machine learning.
Desenvolvimento de Modelos de Machine Learning
Este curso abrangente fornece um guia prático para o desenvolvimento de modelos tradicionais de machine learning no Databricks, com ênfase em demonstrações práticas e workflows utilizando bibliotecas populares de ML. Os participantes irão explorar técnicas-chave de ML, incluindo regressão e clustering, aproveitando as poderosas capacidades do Databricks. O curso abrange a integração com MLflow para acompanhamento de modelos, o Databricks Feature Store para gerenciamento de recursos, e o Optuna para ajuste de hiperparâmetros. Além disso, os participantes aprenderão como acelerar o desenvolvimento de modelos com o Genie Code, o assistente de codificação baseado em IA do Databricks, que utiliza linguagem natural, conexões MCP, instruções e habilidades para guiar o ciclo de vida completo de ML. Ao final do curso, os participantes terão habilidades práticas e aplicáveis ao mundo real para desenvolver, otimizar e implantar modelos de machine learning de forma eficiente no ambiente Databricks.
Implementação de Modelos de Machine Learning
Este curso foi desenvolvido para apresentar três estratégias principais de implantação de machine learning e ilustrar a implementação de cada estratégia no Databricks. Após uma exploração dos fundamentos de implantação de modelos, o curso aprofunda-se na inferência em lotes, oferecendo demonstrações práticas e laboratórios para utilização de um modelo em cenários de inferência em lotes, juntamente com considerações para otimização de desempenho. A segunda parte do curso aborda de forma abrangente a implantação de pipeline, enquanto o segmento final concentra-se na implantação em tempo real. Os participantes realizarão demonstrações práticas e laboratórios, implantando modelos com Model Serving e utilizando o endpoint de serviço para inferência em tempo real.
Operações de Machine Learning
Este curso irá guiar os participantes por uma exploração abrangente das operações de modelo do machine learning, com foco em MLOps e gerenciamento do ciclo de vida do modelo. O segmento inicial aborda os componentes essenciais de MLOps e as melhores práticas, fornecendo aos participantes uma base sólida para operacionalizar modelos do machine learning de forma eficaz. Na parte final do curso, aprofundaremos os conceitos básicos do ciclo de vida do modelo, demonstrando como navegá-lo de forma fluida utilizando o Model Registry em conjunto com o Unity Catalog para um gerenciamento eficiente de modelos. Ao término do curso, os participantes terão adquirido insights práticos e uma compreensão abrangente dos princípios de MLOps, equipados com as habilidades necessárias para navegar pelo intrincado cenário das operações de modelo do machine learning.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28355","entityUrl":{"path":"/br/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-portuguese-br-3377"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-portuguese-br-3377"}}],"nid":28355,"vid":217660,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Portuguese BR","price":"75.00","duration":14400,"body":{"processed":"Este curso oferece uma compreensão abrangente do Spark Structured Streaming e do Delta Lake, incluindo modelos de compute, configuração para leitura de dados em tempo real e manutenção da qualidade dos dados num ambiente de transmissão.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28076","entityUrl":{"path":"/br/training/catalog/aibi-for-data-analysts-portuguese-br-4016"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/aibi-for-data-analysts-portuguese-br-4016"}}],"nid":28076,"vid":217381,"title":"AI/BI for Data Analysts - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso ensina os analistas de dados a projetar, criar, publicar e operar AI/BI Dashboards no Databricks. Os AI/BI Dashboards combinam dados governados pelo Unity Catalog com visualizações interativas, filtros e integração com o Genie, para que os usuários de negócios possam explorar respostas sem escrever código.
O curso segue uma única construção de ponta a ponta. Você começa com tabelas de origem no Unity Catalog e termina com um dashboard de várias páginas publicado e monitorado. Ao longo do caminho, você aprende como os dashboards se encaixam na família mais ampla de produtos AI/BI do Databricks e onde o Genie, os conjuntos de dados, as visualizações e os filtros se encaixam no fluxo de trabalho.
O conteúdo aborda:
• Os fundamentos dos AI/BI Dashboards e como eles se relacionam com o Genie e com o restante da plataforma Databricks.
• A exploração de dados de origem no Unity Catalog e o design de conjuntos de dados reutilizáveis para dashboards com SQL.
• A criação de visualizações (KPIs, tendências, detalhamentos) e a organização de um dashboard de várias páginas bem estruturado.
• O uso do Genie Code para esboçar SQL, gráficos e filtros a partir de prompts em linguagem natural.
• A adição de filtros para tornar os dashboards interativos e responsivos às perguntas de quem os visualiza.
• A publicação, o compartilhamento e o gerenciamento de permissões para que as pessoas certas possam visualizar e editar o dashboard.
• A execução do dashboard em produção com atualização agendada, cache e monitoramento de uso.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-14T09:00:00"},"endDate":{"value":"2026-10-14T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-11T09:00:00"},"endDate":{"value":"2026-11-11T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-05T09:00:00"},"endDate":{"value":"2027-01-05T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28263","entityUrl":{"path":"/br/training/catalog/data-analysis-with-databricks-portuguese-br-2614"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-analysis-with-databricks-portuguese-br-2614"}}],"nid":28263,"vid":217568,"title":"Data Analysis with Databricks - Portuguese BR","price":"1000.00","duration":28800,"body":{"processed":"Este curso fornece uma introdução abrangente ao Databricks SQL. Os alunos irão ingerir dados, escrever queries, produzir visualizações e painéis e configurar alertas. Este curso irá prepará-lo para fazer o exame Analista Associado de Dados, Certificado da Databricks. Este curso é composto por dois módulos de quatro horas.
SQL Analytics on Databricks
Neste curso, você aprenderá a usar efetivamente a Databricks para análise de dados, com foco específico no Databricks SQL. Como Analista de Dados da Databricks, suas responsabilidades incluirão encontrar dados relevantes, analisá-los para possíveis aplicações e transformá-los em formatos que forneçam percepções de negócios valiosos.
Você também entenderá sua função no gerenciamento de objetos de dados e como manipulá-los na Databricks Data Intelligence Platform, usando ferramentas como Notebooks, Editor SQL e Databricks SQL.
Além disso, você aprenderá sobre a importância do Unity Catalog no gerenciamento de ativos de dados e da plataforma como um todo. Por fim, o curso fornecerá uma visão geral de como o Databricks facilita a otimização de desempenho e ensinará como acessar percepções de query para entender os processos que ocorrem nos bastidores ao executar a analítica SQL no Databricks.
AI/BI for Data Analysts
Este curso ensina os analistas de dados a projetar, criar, publicar e operar AI/BI Dashboards no Databricks. Os AI/BI Dashboards combinam dados governados pelo Unity Catalog com visualizações interativas, filtros e integração com o Genie, para que os usuários de negócios possam explorar respostas sem escrever código.
O curso segue uma única construção de ponta a ponta. Você começa com tabelas de origem no Unity Catalog e termina com um dashboard de várias páginas publicado e monitorado. Ao longo do caminho, você aprende como os dashboards se encaixam na família mais ampla de produtos AI/BI do Databricks e onde o Genie, os conjuntos de dados, as visualizações e os filtros se encaixam no fluxo de trabalho.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28357","entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3394"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-portuguese-br-3394"}}],"nid":28357,"vid":217662,"title":"Get Started with SQL Analytics and BI on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta o Databricks Data Intelligence Platform e as habilidades essenciais que um analista de dados precisa para o trabalho diário de analítica SQL e BI. Você navegará pelo workspace e pelo Unity Catalog, escreverá consultas SQL em tabelas gerenciadas pelo Unity Catalog a partir de um Serverless SQL Warehouse, usará o Genie Code para gerar e depurar SQL, trabalhará com o Delta Lake (DML, histórico de versões, viagem do tempo e restauração), criará e publicará Painel de AI/BI, e criará Genie Agents para analítica conversacional.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-30T09:00:00"},"endDate":{"value":"2026-10-30T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-12T09:00:00"},"endDate":{"value":"2026-11-12T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-17T09:00:00"},"endDate":{"value":"2026-12-17T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-14T09:00:00"},"endDate":{"value":"2027-01-14T11:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28087","entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4057"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4057"}}],"nid":28087,"vid":217392,"title":"SQL Analytics on Databricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá a usar efetivamente a Databricks para análise de dados, com foco específico no Databricks SQL. Como Analista de Dados da Databricks, suas responsabilidades incluirão encontrar dados relevantes, analisá-los para possíveis aplicações e transformá-los em formatos que forneçam percepções de negócios valiosos.
Você também entenderá sua função no gerenciamento de objetos de dados e como manipulá-los na Databricks Data Intelligence Platform, usando ferramentas como Notebooks, Editor SQL e Databricks SQL.
Além disso, você aprenderá sobre a importância do Unity Catalog no gerenciamento de ativos de dados e da plataforma como um todo. Por fim, o curso fornecerá uma visão geral de como o Databricks facilita a otimização de desempenho e ensinará como acessar percepções de query para entender os processos que ocorrem nos bastidores ao executar a analítica SQL no Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-13T09:00:00"},"endDate":{"value":"2026-10-13T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-10T09:00:00"},"endDate":{"value":"2026-11-10T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-07T09:00:00"},"endDate":{"value":"2027-01-07T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28287","entityUrl":{"path":"/br/training/catalog/agent-evaluation-on-databricks-portuguese-br-2856"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/agent-evaluation-on-databricks-portuguese-br-2856"}}],"nid":28287,"vid":217592,"title":"Agent Evaluation on Databricks - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso ensina os alunos a avaliar sistematicamente os agentes de IA usando a framework de avaliação do MLflow, abordando os desafios exclusivos dos sistemas de IA não determinísticos que os testes de software tradicionais não conseguem lidar. Os alunos aprendem a implementar várias abordagens de avaliação, incluindo judges integrados para critérios comuns, como correção e segurança, guideline judges para requisitos específicos de negócios e judges personalizados para necessidades especializadas. O curso abrange avaliação off-line usando datasets selecionados e monitoramento de produção on-line, com experiência prática usando as capacidades de MLflow tracing para entender os padrões de execução do agente e coletar feedback humano de diferentes tipos de partes interessadas. Por meio de demonstrações práticas e laboratórios, os alunos desenvolvem habilidades na criação de fluxos de trabalho de avaliação que impulsionam melhorias contínuas de qualidade em todo o ciclo de vida de desenvolvimento de AI agent.
Observação: A Databricks Academy está a migrar para um formato baseado em notebooks para as aulas dentro do ambiente Databricks, descontinuando o uso de diapositivos nas aulas. Pode aceder aos notebooks das aulas no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-17T09:00:00"},"endDate":{"value":"2026-11-17T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-12T09:00:00"},"endDate":{"value":"2027-01-12T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28395","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3577"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3577"}}],"nid":28395,"vid":217700,"title":"Get Started with Databricks for Machine Learning - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, você desenvolverá as habilidades básicas necessárias para usar a Databricks Data Intelligence Platform para executar fluxos de trabalho básicos de machine learning e dar suporte a cargas de trabalho de ciência de dados. Você explorará a plataforma da perspectiva de um profissional de machine learning, abordando tópicos como engenharia de recursos com o Databricks Notebooks e acompanhamento do ciclo de vida do modelo com o MLflow. Além disso, você aprenderá sobre inferência de modelo em tempo real com o Mosaic AI Model Serving e experimentará a abordagem de \"caixa de vidro\" da Databricks para o desenvolvimento de modelos por meio do AutoML. O curso inclui três demonstrações conduzidas por instrutores, culminando em um laboratório abrangente que reforça os conceitos abordados nas demonstrações.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28096","entityUrl":{"path":"/br/training/catalog/data-modeling-strategies-portuguese-br-4105"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-modeling-strategies-portuguese-br-4105"}}],"nid":28096,"vid":217401,"title":"Data Modeling Strategies - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, você aprenderá a projetar modelos de dados escaláveis e prontos para análise usando a Plataforma Databricks Lakehouse. O curso é estruturado em três módulos que abrangem princípios fundamentais de modelagem de dados, casos de uso avançados de warehousing e machine learning e design moderno de produtos de dados. Você explorará as principais metodologias, como o CIF da Inmon, a modelagem dimensional da Kimball e o Data Vault 2.0, juntamente com demonstrações práticas sobre a implementação dessas estratégias no Databricks.
Por meio de laboratórios práticos, você criará diagramas de ER, aplicará transformações SCD Tipo 2 e criará repositórios de recursos para fluxos de trabalho de ML. O curso também apresenta o conceito de produtos de dados e como o pensamento do produto, a governança e a consistência semântica permitem a integração escalável entre domínios. Ao final do curso, você estará equipado para modelar, gerenciar e operacionalizar dados de forma eficaz em uma arquitetura unificada do Lakehouse.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-19T09:00:00"},"endDate":{"value":"2026-11-19T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2027-01-14T09:00:00"},"endDate":{"value":"2027-01-14T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28293","entityUrl":{"path":"/br/training/catalog/data-ingestion-with-lakeflow-connect-portuguese-br-2868"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-ingestion-with-lakeflow-connect-portuguese-br-2868"}}],"nid":28293,"vid":217598,"title":"Data Ingestion with Lakeflow Connect - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso oferece uma introdução abrangente ao LakeFlow Connect, uma solução escalável e simplificada para ingestão de dados no Databricks a partir de uma ampla variedade de fontes. Você começará explorando os diferentes tipos de conectores do LakeFlow Connect (Standard e Managed) e aprenderá diversas técnicas de ingestão de dados, incluindo ingestão em lotes, em lotes incremental e por transmissão. Você também revisará os principais benefícios do uso da Tabela Delta e da Arquitetura Medallion.
Em seguida, você desenvolverá habilidades práticas para ingestão de dados de armazenamento de objetos cloud usando os Conectores Standard do LakeFlow Connect. Isso inclui o uso de métodos como CREATE TABLE AS SELECT (CTAS), COPY INTO e Auto Loader, com ênfase nos benefícios e considerações de cada abordagem. Você também aprenderá como adicionar colunas de metadados às suas tabelas de nível Bronze durante a ingestão na Databricks Data Intelligence Platform. O curso aborda ainda como lidar com registros que não correspondem ao esquema da sua tabela usando a coluna de dados recuperados, juntamente com estratégias para gerenciar e analisar esses dados. Você também explorará técnicas para ingestão e achatamento de dados JSON semiestruturados.
Em seguida, você explorará como realizar ingestão de dados em nível empresarial usando os Conectores Managed do LakeFlow Connect para trazer dados de bancos de dados e aplicações Software-as-a-Service (SaaS). O curso também apresenta o Partner Connect como uma opção para integrar ferramentas de parceiros às suas cargas de trabalho de ingestão.
Por fim, o curso encerra com estratégias alternativas de ingestão, incluindo operações MERGE INTO e o uso do Databricks Marketplace, equipando você com uma base sólida para suportar casos de uso modernos de engenharia de dados.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28396","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3578"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-machine-learning-portuguese-br-3578"}}],"nid":28396,"vid":217701,"title":"Get Started with Databricks for Machine Learning - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você desenvolverá as habilidades básicas necessárias para usar a Databricks Data Intelligence Platform para executar fluxos de trabalho básicos de machine learning e dar suporte a cargas de trabalho de ciência de dados. Você explorará a plataforma da perspectiva de um profissional de machine learning, abordando tópicos como engenharia de recursos com o Databricks Notebooks e acompanhamento do ciclo de vida do modelo com o MLflow. Além disso, você aprenderá sobre inferência de modelo em tempo real com o Mosaic AI Model Serving e experimentará a abordagem de \"caixa de vidro\" da Databricks para o desenvolvimento de modelos por meio do AutoML. O curso inclui três demonstrações conduzidas por instrutores, culminando em um laboratório abrangente que reforça os conceitos abordados nas demonstrações.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"28106","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-4196"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-warehousing-portuguese-br-4196"}}],"nid":28106,"vid":217411,"title":"Get Started with Databricks for Data Warehousing - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece uma visão geral abrangente e prática da abordagem moderna do Databricks para data warehousing, destacando como uma arquitetura data lakehouse combina os pontos fortes dos data warehouses tradicionais com a flexibilidade e escalabilidade do cloud. Trabalhando de ponta a ponta com um varejista fictício (Vintage Audio Co.), você irá explorar o workspace, executar queries em tabelas governadas do Unity Catalog, manter as tabelas gerenciadas do Unity Catalog otimizadas para leituras analíticas, carregar dados de forma incremental com o Auto Loader, modelar um esquema estrela e entregar insights consistentes por meio de visualizações de métricas do Unity Catalog — tudo isso em um único ambiente governado, com recursos orientados por IA (Predictive Optimization, Genie Code) integrados ao longo de todo o processo.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Languages Available: English | 日本語 | Português BR| 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28296","entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-portuguese-br-2874"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-portuguese-br-2874"}}],"nid":28296,"vid":217601,"title":"Build Data Pipelines with Apache Spark™ Declarative Pipelines - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso apresenta aos usuários os conceitos e habilidades essenciais para construir pipelines de dados usando Apache Spark™ Declarative Pipelines (SDP) no Databricks para ingestão e processamento incremental em lotes ou transmissão por meio de múltiplas tabelas de transmissão e visualizações materializadas. Desenvolvido para engenheiros de dados que estão começando com Spark Declarative Pipelines, o curso oferece uma visão abrangente dos componentes principais, como processamento incremental de dados, tabelas de transmissão, visualizações materializadas e visualizações temporárias, destacando seus propósitos específicos e diferenças.
Os tópicos abordados incluem:
• Desenvolvimento e depuração de pipelines ETL com o editor de múltiplos arquivos no Spark Declarative Pipelines usando SQL (com exemplos de código em Python fornecidos)
• Como o Spark Declarative Pipelines rastreia dependências de dados em um pipeline por meio do gráfico do pipeline
• Configuração de recurso de compute do pipeline, ativos de dados, modos de gatilho e outras opções avançadas
Em seguida, o curso apresenta as expectativas de qualidade de dados no Spark Declarative Pipelines, orientando os usuários no processo de integração de expectativas aos pipelines para validar e garantir a integridade de dados. Os alunos irão então Explorar como colocar um pipeline em produção, incluindo opções de agendamento e habilitação do registro de eventos do pipeline para monitorar o desempenho e a integridade do pipeline.
Por fim, o curso aborda como implementar change data capture (CDC) usando a sintaxe AUTO CDC INTO dentro do Spark Declarative Pipelines para gerenciar slowly changing dimensions (SCD Tipo 1 e Tipo 2), preparando os usuários para integrar CDC em seus próprios pipelines.
Nota: a Databricks Academy está migrando para um formato baseado em notebooks nas sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de lab do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-03T09:00:00"},"endDate":{"value":"2026-11-03T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-08T09:00:00"},"endDate":{"value":"2026-12-08T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28407","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3669"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-generative-ai-portuguese-br-3669"}}],"nid":28407,"vid":217712,"title":"Get Started with Databricks for Generative AI - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece uma introdução prática ao Databricks Data Intelligence Platform, com foco em seus principais componentes e recursos para criação e implantação de sistemas de IA generativa. Os participantes aprenderão como o Databricks facilita o desenvolvimento de soluções escaláveis de IA generativa e explorarão ferramentas como AI Search, o Agent Framework e as capacidades de IA generativa do MLflow para acompanhamento e registro de modelos. Este curso inclui experiência prática na construção e avaliação de pipelines de Retrieval-Augmented Generation (RAG), implantação de agentes de IA generativa e uso de frameworks de avaliação para otimizar o desempenho. Ao final do curso, os alunos estarão equipados com as habilidades necessárias para projetar, implantar e monitorar aplicações comuns de IA generativa no Databricks Data Intelligence Platform.
Pode criar umaconta Databricks Free Edition e experimentar as demonstrações subsequentes num ambiente prático.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-15T09:00:00"},"endDate":{"value":"2026-10-15T11:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28110","entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4206"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4206"}}],"nid":28110,"vid":217415,"title":"SQL Analytics on Databricks - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, você aprenderá a usar efetivamente a Databricks para análise de dados, com foco específico no Databricks SQL. Como Analista de Dados da Databricks, suas responsabilidades incluirão encontrar dados relevantes, analisá-los para possíveis aplicações e transformá-los em formatos que forneçam percepções de negócios valiosos.
Você também entenderá sua função no gerenciamento de objetos de dados e como manipulá-los na Databricks Data Intelligence Platform, usando ferramentas como Notebooks, Editor SQL e Databricks SQL.
Além disso, você aprenderá sobre a importância do Unity Catalog no gerenciamento de ativos de dados e da plataforma como um todo. Por fim, o curso fornecerá uma visão geral de como o Databricks facilita a otimização de desempenho e ensinará como acessar percepções de query para entender os processos que ocorrem nos bastidores ao executar a analítica SQL no Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
O curso Deploy Workloads with Lakeflow Jobs ensina como orquestrar e automatizar fluxos de trabalho de dados, analítica e IA usando Lakeflow Jobs como uma plataforma de orquestração unificada dentro do ecossistema Databricks.
• Você aprenderá a projetar e implementar cargas de trabalho de dados usando Grafos Acíclicos Dirigidos (DAGs), configurar diversas opções de agendamento e implementar recursos avançados de fluxo de trabalho, como execução condicional de tarefas, dependências run-if e loops for each.
• O curso aborda as melhores práticas para criar pipelines robustos e prontos para produção com seleção adequada de compute, orquestração modular, técnicas de tratamento de erros e design tolerante a falhas — tudo nativamente integrado na Databricks Data Intelligence Platform.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-09T14:00:00"},"endDate":{"value":"2026-12-09T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28437","entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3907"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3907"}}],"nid":28437,"vid":217742,"title":"DevOps Essentials for Data Engineering - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso explora as melhores práticas de engenharia de software e os princípios de DevOps, projetado especificamente para engenheiros de dados que trabalham com Databricks. Os participantes desenvolverão uma base sólida em tópicos key como qualidade de código, controle de versão, documentação e testes. O curso enfatiza o DevOps, abordando seus componentes principais, benefícios e o papel da integração e entrega contínuas (CI/CD) na otimização dos Workflows de engenharia de dados.
Você aprenderá como aplicar princípios de modularidade no PySpark para criar componentes reutilizáveis e estruturar o código de forma eficiente. A experiência prática inclui o design e a implementação de testes unitários para funções PySpark usando o Framework pytest, seguidos de testes de integração para pipelines de dados Databricks com Spark Declarative Pipeline e Jobs para garantir a confiabilidade.
O curso também aborda as operações essenciais de Git dentro do Databricks, incluindo o uso do Databricks Git Folders para integrar práticas de integração contínua. Por fim, você terá uma visão geral dos diversos métodos de implantação para ativos Databricks, como REST API, CLI, SDK e Declarative Automation Bundles (DABs), fornecendo o conhecimento das técnicas necessárias para implantar e gerenciar seus pipelines.
Ao final do curso, você estará proficiente nas melhores práticas de engenharia de software e DevOps, capacitando-o a construir soluções de engenharia de dados escaláveis, de fácil manutenção e eficientes.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, deixando de usar apresentações de slides para as palestras. Você pode acessar os cadernos das palestras no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-10T09:00:00"},"endDate":{"value":"2026-12-10T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28111","entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4207"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/sql-analytics-on-databricks-portuguese-br-4207"}}],"nid":28111,"vid":217416,"title":"SQL Analytics on Databricks - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você aprenderá a usar efetivamente a Databricks para análise de dados, com foco específico no Databricks SQL. Como Analista de Dados da Databricks, suas responsabilidades incluirão encontrar dados relevantes, analisá-los para possíveis aplicações e transformá-los em formatos que forneçam percepções de negócios valiosos.
Você também entenderá sua função no gerenciamento de objetos de dados e como manipulá-los na Databricks Data Intelligence Platform, usando ferramentas como Notebooks, Editor SQL e Databricks SQL.
Além disso, você aprenderá sobre a importância do Unity Catalog no gerenciamento de ativos de dados e da plataforma como um todo. Por fim, o curso fornecerá uma visão geral de como o Databricks facilita a otimização de desempenho e ensinará como acessar percepções de query para entender os processos que ocorrem nos bastidores ao executar a analítica SQL no Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28303","entityUrl":{"path":"/br/training/catalog/data-engineering-with-databricks-portuguese-br-2932"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-engineering-with-databricks-portuguese-br-2932"}}],"nid":28303,"vid":217608,"title":"Data Engineering with Databricks - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Este é um curso introdutório que serve como um ponto de entrada adequado para aprender Data Engineering com o Databricks.
A seguir, descrevemos cada um dos quatro módulos de quatro horas incluídos neste curso.
Nota: para os quatro módulos a seguir, a Databricks Academy está migrando para um formato baseado em notebooks nas sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides nas aulas. Você pode acessar os notebooks das aulas no ambiente de lab do Vocareum.
1. Data Ingestion with Lakeflow Connect
Este curso oferece uma introdução abrangente ao Lakeflow Connect, uma solução escalável e simplificada para ingerir dados no Databricks a partir de uma ampla variedade de fontes. Você começará explorando os diferentes tipos de conectores do Lakeflow Connect (Standard e Managed) e aprenderá diversas técnicas de ingestão de dados, incluindo ingestão em batch, batch incremental e streaming. Você também revisará os principais benefícios do uso da Delta table e da arquitetura Medallion.
Em seguida, você desenvolverá habilidades práticas para ingerir dados do cloud object storage usando os Lakeflow Connect Standard Connectors. Isso inclui trabalhar com métodos como CREATE TABLE AS SELECT (CTAS), COPY INTO e Auto Loader, com ênfase nos benefícios e nas considerações de cada abordagem. Você também aprenderá a acrescentar colunas de metadados às suas tabelas de nível bronze durante a ingestão na Databricks Data Intelligence Platform. O curso aborda então como lidar com registros que não correspondem ao schema da sua tabela usando a coluna rescued data, além de estratégias para gerenciar e analisar esses dados. Você também explorará técnicas para ingerir e achatar dados JSON semiestruturados.
Depois disso, você explorará como realizar ingestão de dados de nível empresarial usando os Lakeflow Connect Managed Connectors para trazer dados de bancos de dados e aplicações Software-as-a-Service (SaaS). O curso também apresenta o Partner Connect como uma opção para integrar ferramentas de parceiros às suas cargas de trabalho de ingestão.
Por fim, o curso é encerrado com estratégias alternativas de ingestão, incluindo operações MERGE INTO e o uso do Databricks Marketplace, proporcionando uma base sólida para dar suporte a casos de uso modernos de data engineering.
2. Deploy Workloads with Lakeflow Jobs
O curso Deploy Workloads with Lakeflow Jobs ensina como orquestrar e automatizar fluxos de trabalho de dados, analytics e IA usando o Lakeflow Jobs como uma plataforma de orquestração unificada dentro do ecossistema Databricks.
• Você aprenderá a projetar e implementar cargas de trabalho de dados usando Directed Acyclic Graphs (DAGs), configurar várias opções de agendamento e implementar recursos avançados de fluxo de trabalho, como execução condicional de tarefas, dependências run-if e loops for each.
• O curso aborda as práticas recomendadas para criar pipelines robustos e prontos para produção, com seleção adequada de compute, orquestração modular, técnicas de tratamento de erros e design tolerante a falhas — tudo integrado nativamente à Databricks Data Intelligence Platform.
3. Build Data Pipelines with Apache Spark Declarative Pipelines
Este curso apresenta aos usuários os conceitos e as habilidades essenciais necessários para criar pipelines de dados usando o Apache Spark Declarative Pipelines (SDP) no Databricks para ingestão e processamento em batch incremental ou streaming por meio de várias streaming tables e materialized views. Projetado para data engineers iniciantes no Spark Declarative Pipelines, o curso oferece uma visão geral abrangente de componentes essenciais, como processamento incremental de dados, streaming tables, materialized views e temporary views, destacando seus propósitos específicos e suas diferenças.
Os tópicos abordados incluem:
• Desenvolvimento e depuração de pipelines de ETL com o editor multiarquivo do Spark Declarative Pipelines usando SQL (com exemplos de código em Python fornecidos)
• Como o Spark Declarative Pipelines rastreia as dependências de dados em um pipeline por meio do pipeline graph
• Configuração de recursos de compute do pipeline, ativos de dados, modos de acionamento e outras opções avançadas
Em seguida, o curso apresenta as data quality expectations no Spark Declarative Pipelines, orientando os usuários no processo de integração de expectations aos pipelines para validar e impor a integridade dos dados. Os alunos exploram então como colocar um pipeline em produção, incluindo opções de agendamento, e como habilitar o registro de eventos do pipeline para monitorar seu desempenho e sua integridade.
Por fim, o curso aborda como implementar Change Data Capture (CDC) usando a sintaxe AUTO CDC INTO no Spark Declarative Pipelines para gerenciar slowly changing dimensions (SCD Type 1 e Type 2), preparando os usuários para integrar o CDC aos seus próprios pipelines.
4. DevOps Essentials for Data Engineering
Este curso explora as práticas recomendadas de engenharia de software e os princípios de DevOps, especificamente desenvolvidos para data engineers que trabalham com o Databricks. Os participantes construirão uma base sólida em tópicos-chave, como qualidade de código, controle de versão, documentação e testes. O curso enfatiza o DevOps, abordando seus componentes essenciais, benefícios e o papel da integração e entrega contínuas (CI/CD) na otimização dos fluxos de trabalho de data engineering.
Você aprenderá a aplicar princípios de modularidade no PySpark para criar componentes reutilizáveis e estruturar o código de forma eficiente. A experiência prática inclui projetar e implementar testes unitários para funções do PySpark usando o framework pytest, seguidos de testes de integração para pipelines de dados do Databricks com Spark Declarative Pipeline e Jobs para garantir a confiabilidade.
O curso também aborda operações essenciais do Git no Databricks, incluindo o uso das Databricks Git Folders para integrar práticas de integração contínua. Por fim, você terá uma visão geral de vários métodos de deployment de ativos do Databricks, como REST API, CLI, SDK e Declarative Automation Bundles (DABs), proporcionando o conhecimento das técnicas para fazer o deployment e gerenciar seus pipelines.
Ao final do curso, você dominará as práticas recomendadas de engenharia de software e DevOps, o que lhe permitirá criar soluções de data engineering escaláveis, fáceis de manter e eficientes.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28441","entityUrl":{"path":"/br/training/catalog/automated-deployment-with-declarative-automation-bundles-portuguese-br-3915"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/automated-deployment-with-declarative-automation-bundles-portuguese-br-3915"}}],"nid":28441,"vid":217746,"title":"Automated Deployment with Declarative Automation Bundles - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso oferece uma revisão abrangente dos princípios de DevOps e sua aplicação a projetos Databricks. Ele começa com uma visão geral dos conceitos fundamentais de DevOps, DataOps, integração contínua (CI), implantação contínua (CD) e testes, e explora como esses princípios podem ser aplicados a pipelines de engenharia de dados.
O curso então se concentra na implantação contínua dentro do processo de CI/CD, examinando ferramentas como a REST API, o SDK e o CLI do Databricks para implantação de projetos. Você aprenderá sobre os Declarative Automation Bundles (DABs) e como eles se encaixam no processo de CI/CD. Você irá explorar seus principais componentes, estrutura de pastas e como eles simplificam a implantação em diversos ambientes de destino no Databricks. Você também aprenderá como adicionar variáveis, modificar, validar, implantar e executar Declarative Automation Bundles para múltiplos ambientes com diferentes configurações usando o Databricks CLI.
Por fim, o curso apresenta o Visual Studio Code como um Ambiente de Desenvolvimento Interativo (IDE) para construir, testar e implantar Declarative Automation Bundles localmente, otimizando seu processo de desenvolvimento. O curso é concluído com uma introdução à automação de pipelines de implantação usando GitHub Actions para aprimorar o fluxo de trabalho de CI/CD com Declarative Automation Bundles.
Ao final deste curso, você estará preparado para automatizar implantações de projetos Databricks com Declarative Automation Bundles, melhorando a eficiência por meio de práticas de DevOps.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28128","entityUrl":{"path":"/br/training/catalog/data-modeling-strategies-portuguese-br-4265"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-modeling-strategies-portuguese-br-4265"}}],"nid":28128,"vid":217433,"title":"Data Modeling Strategies - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Neste curso, você aprenderá a projetar modelos de dados escaláveis e prontos para análise usando a Plataforma Databricks Lakehouse. O curso é estruturado em três módulos que abrangem princípios fundamentais de modelagem de dados, casos de uso avançados de warehousing e machine learning e design moderno de produtos de dados. Você explorará as principais metodologias, como o CIF da Inmon, a modelagem dimensional da Kimball e o Data Vault 2.0, juntamente com demonstrações práticas sobre a implementação dessas estratégias no Databricks.
Por meio de laboratórios práticos, você criará diagramas de ER, aplicará transformações SCD Tipo 2 e criará repositórios de recursos para fluxos de trabalho de ML. O curso também apresenta o conceito de produtos de dados e como o pensamento do produto, a governança e a consistência semântica permitem a integração escalável entre domínios. Ao final do curso, você estará equipado para modelar, gerenciar e operacionalizar dados de forma eficaz em uma arquitetura unificada do Lakehouse.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28315","entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-2999"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-2999"}}],"nid":28315,"vid":217620,"title":"Databricks Performance Optimization - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Neste curso, aprenderá como otimizar as cargas de trabalho e o layout físico com o Spark e o Delta Lake, bem como analisar a interface do utilizador do Spark para avaliar o desempenho e depurar aplicações. Abordaremos temas como transmissão, net clustering, data skipping, cache, photons e muito mais.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-12T09:00:00"},"endDate":{"value":"2026-11-12T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28475","entityUrl":{"path":"/br/training/catalog/generative-ai-fundamentals-accreditation-portuguese-br-2310"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/generative-ai-fundamentals-accreditation-portuguese-br-2310"}}],"nid":28475,"vid":217780,"title":"Generative AI Fundamentals Accreditation - Portuguese BR","price":"0.00","duration":900,"body":{"processed":"Esta é uma avaliação de 20 minutos que testará seus conhecimentos em conceitos fundamentais relacionados à Inteligência Artificial Generativa.
Após concluir com sucesso esta avaliação, você receberá a insígnia de Fundamentos de IA Generativa da Databricks.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
Neste curso, você aprenderá a projetar modelos de dados escaláveis e prontos para análise usando a Plataforma Databricks Lakehouse. O curso é estruturado em três módulos que abrangem princípios fundamentais de modelagem de dados, casos de uso avançados de warehousing e machine learning e design moderno de produtos de dados. Você explorará as principais metodologias, como o CIF da Inmon, a modelagem dimensional da Kimball e o Data Vault 2.0, juntamente com demonstrações práticas sobre a implementação dessas estratégias no Databricks.
Por meio de laboratórios práticos, você criará diagramas de ER, aplicará transformações SCD Tipo 2 e criará repositórios de recursos para fluxos de trabalho de ML. O curso também apresenta o conceito de produtos de dados e como o pensamento do produto, a governança e a consistência semântica permitem a integração escalável entre domínios. Ao final do curso, você estará equipado para modelar, gerenciar e operacionalizar dados de forma eficaz em uma arquitetura unificada do Lakehouse.
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2668,"name":"Data Architect"}},"sessions":[]},{"id":"28318","entityUrl":{"path":"/br/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-portuguese-br-3030"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-portuguese-br-3030"}}],"nid":28318,"vid":217623,"title":"Advanced Techniques with Apache Spark Declarative Pipelines - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso explora o Declarative Pipelines do Apache Spark da Databricks (SDP) para a construção de pipelines de transmissão prontos para produção. Você aprenderá padrões de design avançados, aplicação robusta de qualidade de dados e integração entre plataformas, essenciais para a engenharia lakehouse no mundo real.
Ao longo do curso, você se aprofundará em técnicas modernas de ingestão de dados e processamento, dominando ferramentas como Liquid Clustering para otimização de configuração e o padrão Multiplex Streaming para eventos com esquemas mistos. Ao final dos módulos, você saberá como lidar com confiança com a evolução do esquema, automatizar o Change Data Capture (CDC) e garantir a integridade de dados.
Por meio de aulas e demonstrações práticas, você irá:
• Construir pipelines com múltiplos fluxos para ingerir dados de múltiplas fontes em uma Tabela Bronze unificada.
• Aplicar Liquid Clustering e Expectativas de Qualidade de Dados nas camadas Prata e Ouro.
• Implementar o padrão Multiplex com Iceberg UniForm para acesso a dados entre plataformas.
• Automatizar o acompanhamento de história do SCD Tipo 2 usando AUTO CDC INTO.
• Projetar pipelines de quarentena com zero perda de dados para auditar e gerenciar registros inválidos.
Observação: A Databricks Academy está a migrar para um formato baseado em notebooks para as aulas dentro do ambiente Databricks, descontinuando o uso de diapositivos nas aulas. Pode aceder aos notebooks das aulas no ambiente de laboratório Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28478","entityUrl":{"path":"/br/training/catalog/databricks-fundamentals-accreditation-portuguese-br-2338"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-fundamentals-accreditation-portuguese-br-2338"}}],"nid":28478,"vid":217783,"title":"Databricks Fundamentals Accreditation - Portuguese BR","price":"0.00","duration":1800,"body":{"processed":"Bem-vindo à Certificação Fundamentos da Databricks. Neste quiz de 10 perguntas, vamos testar seus conhecimentos sobre a Plataforma de Inteligência de Dados da Databricks. Ao concluir este quiz com sucesso, você receberá um distintivo (dentro de 48 horas) através de nosso fornecedor de distintivos, Accredible. Boa sorte!
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28157","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4535"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-platform-administration-portuguese-br-4535"}}],"nid":28157,"vid":217462,"title":"Get Started with Databricks Platform Administration - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, você aprenderá os conceitos básicos de administração da plataforma no Databricks Data Intelligence Platform. Ele oferece uma visão abrangente do Unity Catalog, um componente essencial para uma governança de dados eficaz em ambientes Databricks. Dividido em cinco módulos, começa com uma introdução detalhada à infraestrutura Databricks e seu Data Intelligence Platform, incluindo um guia aprofundado do Databricks Workspace. Você explorará os princípios de governança de dados no Unity Catalog, abordando seus conceitos principais, arquitetura e funções. O curso também enfatiza o gerenciamento de metastores e recursos de compute do Unity Catalog, incluindo clusters e SQL warehouses. Por fim, você dominará o controle de acesso a dados aprendendo sobre privilégios, acesso refinado e como governar objetos de dados. Ao final, você estará equipado com habilidades essenciais para administrar o Unity Catalog, implementar uma governança de dados eficaz, otimizar recursos de compute e aplicar estratégias robustas de segurança de dados. Com a aquisição de uma inscrição no Databricks Labs, o curso também é encerrado com um exercício de laboratório abrangente para praticar o que você aprendeu em um ambiente Databricks Workspace real.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2407,"name":"Platform Administrator"}},"sessions":[]},{"id":"28323","entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-3080"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-performance-optimization-portuguese-br-3080"}}],"nid":28323,"vid":217628,"title":"Databricks Performance Optimization - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Neste curso, aprenderá como otimizar as cargas de trabalho e o layout físico com o Spark e o Delta Lake, bem como analisar a interface do utilizador do Spark para avaliar o desempenho e depurar aplicações. Abordaremos temas como transmissão, net clustering, data skipping, cache, photons e muito mais.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28481","entityUrl":{"path":"/br/training/catalog/advanced-data-engineering-with-databricks-portuguese-br-2363"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/advanced-data-engineering-with-databricks-portuguese-br-2363"}}],"nid":28481,"vid":217786,"title":"Advanced Data Engineering with Databricks - Portuguese BR","price":"1500.00","duration":57600,"body":{"processed":"Este curso serve como um ponto de entrada apropriado para aprender Engenharia de Dados Avançada com Databricks. Abaixo, descreveremos cada um dos quatro módulos de quatro horas incluídos neste curso.
Observação: a Databricks Academy está mudando para um formato baseado em cadernos para as aulas presenciais no ambiente Databricks, descontinuando o uso de apresentações de slides nas primeiras módulo. Você pode acessar os cadernos das aulas no ambiente de laboratório Vocareum.
Advanced Techniques with Apache Spark Declarative Pipelines
Este curso explora o Declarative Pipelines do Apache Spark da Databricks (SDP) para a construção de pipelines de transmissão prontos para produção. Você aprenderá padrões de design avançados, aplicação robusta de qualidade de dados e integração entre plataformas, essenciais para a engenharia lakehouse no mundo real.
Ao longo do curso, você se aprofundará em técnicas modernas de ingestão de dados e processamento, dominando ferramentas como Liquid Clustering para otimização de configuração e o padrão Multiplex Streaming para eventos com esquemas mistos. Ao final dos módulos, você saberá como lidar com confiança com a evolução do esquema, automatizar o Change Data Capture (CDC) e garantir a integridade de dados.
Por meio de aulas e demonstrações práticas, você irá:
• Construir pipelines com múltiplos fluxos para ingerir dados de múltiplas fontes em uma Tabela Bronze unificada.
• Aplicar Liquid Clustering e Expectativas de Qualidade de Dados nas camadas Prata e Ouro.
• Implementar o padrão Multiplex com Iceberg UniForm para acesso a dados entre plataformas.
• Automatizar o acompanhamento de história do SCD Tipo 2 usando AUTO CDC INTO.
• Projetar pipelines de quarentena com zero perda de dados para auditar e gerenciar registros inválidos.
Databricks Data Privacy
Este conteúdo oferece um guia completo para a gestão da privacidade de dados no Databricks. Aborda temas essenciais como a arquitetura do Delta Lake, o isolamento regional de dados, a compliance com o RGPD/CCPA e a utilização do Change Data Feed (CDF). Através de demonstrações práticas e laboratórios interativos, os participantes aprendem a utilizar as funcionalidades do Unity Catalog para proteger dados confidenciais e garantir a compliance, capacitando-os para salvaguardar a integridade dos dados de forma eficaz.
Databricks Performance Optimization
Neste curso, aprenderá como otimizar as cargas de trabalho e o layout físico com o Spark e o Delta Lake, bem como analisar a interface do utilizador do Spark para avaliar o desempenho e depurar aplicações. Abordaremos temas como transmissão, net clustering, data skipping, cache, photons e muito mais.
Automated Deployment with Declarative Automation Bundles
Este curso oferece uma revisão abrangente dos princípios de DevOps e sua aplicação a projetos Databricks. Ele começa com uma visão geral dos conceitos fundamentais de DevOps, DataOps, integração contínua (CI), implantação contínua (CD) e testes, e explora como esses princípios podem ser aplicados a pipelines de engenharia de dados.
O curso então se concentra na implantação contínua dentro do processo de CI/CD, examinando ferramentas como a REST API, o SDK e o CLI do Databricks para implantação de projetos. Você aprenderá sobre os Declarative Automation Bundles (DABs) e como eles se encaixam no processo de CI/CD. Você irá explorar seus principais componentes, estrutura de pastas e como eles simplificam a implantação em diversos ambientes de destino no Databricks. Você também aprenderá como adicionar variáveis, modificar, validar, implantar e executar Declarative Automation Bundles para múltiplos ambientes com diferentes configurações usando o Databricks CLI.
Por fim, o curso apresenta o Visual Studio Code como um Ambiente de Desenvolvimento Interativo (IDE) para construir, testar e implantar Declarative Automation Bundles localmente, otimizando seu processo de desenvolvimento. O curso é concluído com uma introdução à automação de pipelines de implantação usando GitHub Actions para aprimorar o fluxo de trabalho de CI/CD com Declarative Automation Bundles.
Ao final deste curso, você estará preparado para automatizar implantações de projetos Databricks com Declarative Automation Bundles, melhorando a eficiência por meio de práticas de DevOps.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28049","entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3922"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3922"}}],"nid":28049,"vid":217354,"title":"DevOps Essentials for Data Engineering - Portuguese BR","price":"75.00","duration":10800,"body":{"processed":"Este curso explora as melhores práticas de engenharia de software e os princípios de DevOps, projetados especificamente para engenheiros de dados que trabalham com Databricks. Os participantes construirão uma base sólida em tópicos-chave, como qualidade de código, controle de versão, documentação e testes. O curso enfatiza o DevOps, abordando os principais componentes, os benefícios e o papel da continuous integration e delivery (CI/CD) na otimização dos fluxos de trabalho de engenharia de dados.
Você aprenderá a aplicar princípios de modularidade no PySpark para criar componentes reutilizáveis e estruturar código de forma eficiente. A experiência prática inclui o projeto e a implementação de testes unitários para funções do PySpark usando a estrutura pytest, seguidos por testes de integração para pipelines de dados Databricks com DLT (Delta Live Tables) e fluxos de trabalho para garantir a confiabilidade.
O curso também aborda operações essenciais do Git no Databricks, incluindo o uso de pastas Git do Databricks para integrar práticas de integração contínua. Por fim, você examinará de alto nível vários métodos de implantação de ativos do Databricks, como REST API, CLI, SDK e DABs (Databricks Asset Bundles), fornecendo o conhecimento de técnicas para implantar e gerenciar seus pipelines.
Ao final do curso, você será proficiente em software engineering e práticas recomendadas de DevOps, permitindo que você crie soluções de engenharia de dados escaláveis, sustentáveis e eficientes.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28189","entityUrl":{"path":"/br/training/catalog/databricks-platform-administration-fundamentals-portuguese-br-4665"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-platform-administration-fundamentals-portuguese-br-4665"}}],"nid":28189,"vid":217494,"title":"Databricks Platform Administration Fundamentals - Portuguese BR","price":"0.00","duration":5400,"body":{"processed":"Neste curso, você aprenderá os fundamentos de administração da plataforma no Databricks Data Intelligence Platform. Ele abrange a arquitetura Databricks, o modelo de segurança, as funções administrativas, o gerenciamento de recursos em cloud e as técnicas de automação. Você explorará as principais responsabilidades administrativas, incluindo o gerenciamento de workspaces, metastores e armazenamento externo, garantindo a segurança por meio de controles de acesso e privilégios baseados em função. Além disso, você aprenderá a automatizar tarefas administrativas usando o Databricks SDK, CLI, e Terraform. O curso inclui demonstrações práticas para reforçar conceitos e simplificar o gerenciamento da plataforma. Ao final, você estará equipado para administrar, proteger e automatizar com eficiência os ambientes Databricks em sua organização.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28326","entityUrl":{"path":"/br/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-portuguese-br-3083"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-streaming-and-lakeflow-spark-declarative-pipelines-portuguese-br-3083"}}],"nid":28326,"vid":217631,"title":"Databricks Streaming and Lakeflow Spark Declarative Pipelines - Portuguese BR","price":"0.00","duration":14400,"body":{"processed":"Este curso oferece uma compreensão abrangente do Spark Structured Streaming e do Delta Lake, incluindo modelos de compute, configuração para leitura de dados em tempo real e manutenção da qualidade dos dados num ambiente de transmissão.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28497","entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-2439"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/get-started-with-databricks-for-data-engineering-portuguese-br-2439"}}],"nid":28497,"vid":217802,"title":"Get Started with Databricks for Data Engineering - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso apresenta as habilidades fundamentais necessárias para executar um fluxo de trabalho básico de engenharia de dados na Databricks Data Intelligence Platform. Você vai explorar o workspace, trabalhar com o Unity Catalog e aprender os blocos de construção que um engenheiro de dados usa no dia a dia no Databricks.
O curso segue um caminho prático. Você começa se familiarizando com o workspace e, em seguida, avança por notebooks de Demo e Lab em pares para cada tópico. As Demos apresentam um conceito com o instrutor ou por meio de um notebook guiado; os Labs pedem que você aplique por conta própria o que acabou de ver.
O conteúdo aborda:
• A Databricks Data Intelligence Platform e como o workspace do Databricks, o Unity Catalog e os notebooks se integram.
• Criação e gerenciamento de tabelas Delta Lake.
• Modificação de dados com INSERT, UPDATE e DELETE.
• Exploração do histórico de versões e do time travel em tabelas Delta.
• Ingestão de dados com as opções do Lakeflow Connect: CTAS, a interface de Upload e COPY INTO.
• Construção de um pipeline de Arquitetura Medallion que transforma dados pelas camadas Bronze, Silver e Gold.
• Automação de pipelines com o Lakeflow Jobs.
• (Bônus) Construção de um pipeline declarativo com o Spark Declarative Pipelines.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-16T09:00:00"},"endDate":{"value":"2026-10-16T11:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-12-11T09:00:00"},"endDate":{"value":"2026-12-11T11:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28050","entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3923"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/devops-essentials-for-data-engineering-portuguese-br-3923"}}],"nid":28050,"vid":217355,"title":"DevOps Essentials for Data Engineering - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso explora as melhores práticas de engenharia de software e os princípios de DevOps, projetados especificamente para engenheiros de dados que trabalham com Databricks. Os participantes construirão uma base sólida em tópicos-chave, como qualidade de código, controle de versão, documentação e testes. O curso enfatiza o DevOps, abordando os principais componentes, os benefícios e o papel da continuous integration e delivery (CI/CD) na otimização dos fluxos de trabalho de engenharia de dados.
Você aprenderá a aplicar princípios de modularidade no PySpark para criar componentes reutilizáveis e estruturar código de forma eficiente. A experiência prática inclui o projeto e a implementação de testes unitários para funções do PySpark usando a estrutura pytest, seguidos por testes de integração para pipelines de dados Databricks com DLT (Delta Live Tables) e fluxos de trabalho para garantir a confiabilidade.
O curso também aborda operações essenciais do Git no Databricks, incluindo o uso de pastas Git do Databricks para integrar práticas de integração contínua. Por fim, você examinará de alto nível vários métodos de implantação de ativos do Databricks, como REST API, CLI, SDK e DABs (Databricks Asset Bundles), fornecendo o conhecimento de técnicas para implantar e gerenciar seus pipelines.
Ao final do curso, você será proficiente em software engineering e práticas recomendadas de DevOps, permitindo que você crie soluções de engenharia de dados escaláveis, sustentáveis e eficientes.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28190","entityUrl":{"path":"/br/training/catalog/databricks-accredited-platform-administrator-accreditation-portuguese-br-4666"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-accredited-platform-administrator-accreditation-portuguese-br-4666"}}],"nid":28190,"vid":217495,"title":"Databricks Accredited Platform Administrator Accreditation - Portuguese BR","price":"0.00","duration":900,"body":{"processed":"O exame Databricks Certified Platform Administrator é um exame de certificação não supervisionado com duração de 20 minutos que avalia os conhecimentos sobre gerenciamento e operação da plataforma Databricks Lakehouse usando o Unity Catalog. Este exame avalia sua capacidade de realizar operações fundamentais de gerenciamento da plataforma, gerenciar identidade e controle de acesso, configurar as definições da plataforma e medidas de segurança, gerenciar recursos de computação, gerenciar e proteger dados dentro da plataforma e gerenciar ferramentas de CI/CD dentro da plataforma. Os candidatos que forem aprovados no exame receberão o selo de Administrador de Plataforma Certificado pela Databricks e um certificado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28338","entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-portuguese-br-3287"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-portuguese-br-3287"}}],"nid":28338,"vid":217643,"title":"Build Data Pipelines with Lakeflow Declarative Pipelines - Portuguese BR","price":"75.00","duration":14400,"body":{"processed":"Este curso apresenta aos usuários os conceitos e habilidades essenciais necessários para criar pipelines de dados usando pipelines declarativos do Lakeflow em Databricks para ingestão e processamento incrementais em lote ou transmissão por meio de várias streaming tables e materialized views. Projetado para engenheiros de dados novos em pipelines declarativos Lakeflow, o curso fornece uma visão geral abrangente dos principais componentes, como processamento incremental de dados, streaming tables, materialized views e views temporárias, destacando suas finalidades e diferenças específicas.
Os tópicos abordados incluem:
- Desenvolvimento e depuração de pipelines ETL com o editor de vários arquivos no Lakeflow usando SQL (com exemplos de código Python fornecidos)
- Como os pipelines declarativos do Lakeflow acompanham dependências de dados em um pipeline através do gráfico de pipeline
- Configuração de recursos de computação do pipeline, ativos de dados, modos de gatilho e outras opções avançadas.
Em seguida, o curso apresenta as expectativas de qualidade de dados no Lakeflow, orientando os usuários pelo processo de integração de expectativas em pipelines para validar e impor a integridade dos dados. Em seguida, os alunos explorarão como colocar um pipeline em produção, incluindo opções de agendamento, modo de produção e habilitação do log de eventos do pipeline para monitorar o desempenho e a integridade do pipeline.
Finalmente, o curso aborda como implementar a captura de dados de alterações (CDC) usando a sintaxe APPLY CHANGES INTO dentro dos Pipelines Declarativos do Lakeflow para gerenciar dimensões que mudam lentamente (SCD Tipo 1 e Tipo 2), preparando os usuários para integrar CDC em seus próprios pipelines.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2408,"name":"Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28066","entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-3973"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/databricks-data-privacy-portuguese-br-3973"}}],"nid":28066,"vid":217371,"title":"Databricks Data Privacy - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este conteúdo oferece um guia completo para a gestão da privacidade de dados no Databricks. Aborda temas essenciais como a arquitetura do Delta Lake, o isolamento regional de dados, a compliance com o RGPD/CCPA e a utilização do Change Data Feed (CDF). Através de demonstrações práticas e laboratórios interativos, os participantes aprendem a utilizar as funcionalidades do Unity Catalog para proteger dados confidenciais e garantir a compliance, capacitando-os para salvaguardar a integridade dos dados de forma eficaz.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28258","entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-2591"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-model-development-portuguese-br-2591"}}],"nid":28258,"vid":217563,"title":"Machine Learning Model Development - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso abrangente fornece um guia prático para o desenvolvimento de modelos tradicionais de machine learning no Databricks, com ênfase em demonstrações práticas e workflows utilizando bibliotecas populares de ML. Os participantes irão explorar técnicas-chave de ML, incluindo regressão e clustering, aproveitando as poderosas capacidades do Databricks. O curso abrange a integração com MLflow para acompanhamento de modelos, o Databricks Feature Store para gerenciamento de recursos, e o Optuna para ajuste de hiperparâmetros. Além disso, os participantes aprenderão como acelerar o desenvolvimento de modelos com o Genie Code, o assistente de codificação baseado em IA do Databricks, que utiliza linguagem natural, conexões MCP, instruções e habilidades para guiar o ciclo de vida completo de ML. Ao final do curso, os participantes terão habilidades práticas e aplicáveis ao mundo real para desenvolver, otimizar e implantar modelos de machine learning de forma eficiente no ambiente Databricks.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-20T09:00:00"},"endDate":{"value":"2026-10-20T13:00:00"},"timezone":"America/Sao_Paulo"}},{"entity":{"startDate":{"value":"2026-11-11T09:00:00"},"endDate":{"value":"2026-11-11T13:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28339","entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-portuguese-br-3289"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/build-data-pipelines-with-lakeflow-declarative-pipelines-portuguese-br-3289"}}],"nid":28339,"vid":217644,"title":"Build Data Pipelines with Lakeflow Declarative Pipelines - Portuguese BR","price":"0.00","duration":14400,"body":{"processed":"Este curso apresenta aos usuários os conceitos e habilidades essenciais necessários para criar pipelines de dados usando pipelines declarativos do Lakeflow em Databricks para ingestão e processamento incrementais em lote ou transmissão por meio de várias streaming tables e materialized views. Projetado para engenheiros de dados novos em pipelines declarativos Lakeflow, o curso fornece uma visão geral abrangente dos principais componentes, como processamento incremental de dados, streaming tables, materialized views e views temporárias, destacando suas finalidades e diferenças específicas.
Os tópicos abordados incluem:
- Desenvolvimento e depuração de pipelines ETL com o editor de vários arquivos no Lakeflow usando SQL (com exemplos de código Python fornecidos)
- Como os pipelines declarativos do Lakeflow acompanham dependências de dados em um pipeline através do gráfico de pipeline
- Configuração de recursos de computação do pipeline, ativos de dados, modos de gatilho e outras opções avançadas.
Em seguida, o curso apresenta as expectativas de qualidade de dados no Lakeflow, orientando os usuários pelo processo de integração de expectativas em pipelines para validar e impor a integridade dos dados. Em seguida, os alunos explorarão como colocar um pipeline em produção, incluindo opções de agendamento, modo de produção e habilitação do log de eventos do pipeline para monitorar o desempenho e a integridade do pipeline.
Finalmente, o curso aborda como implementar a captura de dados de alterações (CDC) usando a sintaxe APPLY CHANGES INTO dentro dos Pipelines Declarativos do Lakeflow para gerenciar dimensões que mudam lentamente (SCD Tipo 1 e Tipo 2), preparando os usuários para integrar CDC em seus próprios pipelines.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28069","entityUrl":{"path":"/br/training/catalog/automated-deployment-with-databricks-asset-bundles-portuguese-br-3997"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/automated-deployment-with-databricks-asset-bundles-portuguese-br-3997"}}],"nid":28069,"vid":217374,"title":"Automated Deployment with Databricks Asset Bundles - Portuguese BR","price":"0.00","duration":7200,"body":{"processed":"Este curso oferece uma revisão abrangente dos princípios de DevOps e sua aplicação em projetos Databricks. Ele começa com uma visão geral dos principais conceitos de DevOps, DataOps, continuous integration (CI), continuous deployment (CD) e testes, e explora como esses princípios podem ser aplicados a pipelines de engenharia de dados.
Em seguida, o curso se concentra na continuous deployment dentro do processo de CI/CD, examinando ferramentas como a Databricks REST API, o SDK e a CLI para a implantação de projetos. Você aprenderá sobre os Databricks Asset Bundles (DABs) e como eles se encaixam no processo de CI/CD. Você se aprofundará em seus principais componentes, estrutura de pastas e como eles otimizam a implantação em vários ambientes de destino na Databricks. Você também aprenderá como adicionar variáveis, modificar, validar, implantar e executar Databricks Asset Bundles para vários ambientes com diferentes configurações usando a Databricks CLI.
Por fim, o curso apresenta o Visual Studio Code como um Interactive Development Environment (IDE) para criar, testar e implantar Databricks Asset Bundles localmente, otimizando seu processo de desenvolvimento. O curso conclui com uma introdução à automação de pipelines de implantação usando o GitHub Actions para aprimorar o fluxo de trabalho de CI/CD com Databricks Asset Bundles.
Ao final deste curso, você estará apto a automatizar implantações de projetos Databricks com Databricks Asset Bundles, melhorando a eficiência por meio de práticas de DevOps.
Nota: Este curso é o quarto da série “Engenharia de dados avançada com Databricks”.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28259","entityUrl":{"path":"/br/training/catalog/machine-learning-model-deployment-portuguese-br-2593"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/machine-learning-model-deployment-portuguese-br-2593"}}],"nid":28259,"vid":217564,"title":"Machine Learning Model Deployment - Portuguese BR","price":"750.00","duration":14400,"body":{"processed":"Este curso foi desenvolvido para apresentar três estratégias principais de implantação de machine learning e ilustrar a implementação de cada estratégia no Databricks. Após uma exploração dos fundamentos de implantação de modelos, o curso aprofunda-se na inferência em lotes, oferecendo demonstrações práticas e laboratórios para utilização de um modelo em cenários de inferência em lotes, juntamente com considerações para otimização de desempenho. A segunda parte do curso aborda de forma abrangente a implantação de pipeline, enquanto o segmento final concentra-se na implantação em tempo real. Os participantes realizarão demonstrações práticas e laboratórios, implantando modelos com Model Serving e utilizando o endpoint de serviço para inferência em tempo real.
Nota: A Databricks Academy está fazendo a transição para um formato baseado em notebooks para as sessões em sala de aula dentro do ambiente Databricks, descontinuando o uso de apresentações de slides para as aulas. Você pode acessar os notebooks de aula no ambiente de laboratório do Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[{"entity":{"startDate":{"value":"2026-11-10T14:00:00"},"endDate":{"value":"2026-11-10T18:00:00"},"timezone":"America/Sao_Paulo"}}]},{"id":"28344","entityUrl":{"path":"/br/training/catalog/data-ingestion-with-delta-lake-portuguese-br-3301"},"entityTranslations":[{"entityLanguage":{"id":"br"},"entityUrl":{"path":"/br/training/catalog/data-ingestion-with-delta-lake-portuguese-br-3301"}}],"nid":28344,"vid":217649,"title":"Data Ingestion with Delta Lake - Portuguese BR","price":"0.00","duration":14400,"body":{"processed":"Este curso prepara profissionais de dados para utilizar a plataforma de inteligência do Databricks e produzir pipelines de ETL. Os alunos usarão Delta Live Tables com Spark SQL e Python para definir e programar pipelines que processam incrementalmente novos dados de uma variedade de fontes de dados no Lakehouse. Os alunos também orquestrarão tarefas com Databricks Workflows e promoverão código com Databricks Repos.
Nota: Este curso faz parte da série de cursos \"Data Engineering Avançada com o Databricks\".
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]}]},"coursesFR":{"entities":[{"id":"33990","entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-6636"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-6636"}}],"nid":33990,"vid":254513,"title":"Deploy Workloads with Lakeflow Jobs - French","price":"0.00","duration":7200,"body":{"processed":"Le cours Deploy Workloads with Lakeflow Jobs enseigne comment orchestrer et automatiser des workflows de données, d'analyse de données et d'IA à l'aide de Lakeflow Jobs en tant que plateforme d'orchestration unifiée au sein de l'écosystème Databricks.
• Vous apprendrez à concevoir et à mettre en œuvre des charges de travail de données à l'aide de graphes orientés acycliques (DAG), à configurer diverses options de planification et à implémenter des fonctionnalités avancées de workflow telles que l'exécution conditionnelle de tâches, les dépendances run-if et les boucles for each.
• Le cours couvre les meilleures pratiques pour créer des pipelines robustes et prêts pour la production, avec une sélection appropriée du compute, une orchestration modulaire, des techniques de gestion des erreurs et une conception tolérante aux pannes — le tout nativement intégré au sein de la Databricks Data Intelligence Platform.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33992","entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-6638"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-6638"}}],"nid":33992,"vid":254515,"title":"Deploy Workloads with Lakeflow Jobs - French","price":"75.00","duration":10800,"body":{"processed":"Le cours Deploy Workloads with Lakeflow Jobs enseigne comment orchestrer et automatiser des workflows de données, d'analyse de données et d'IA à l'aide de Lakeflow Jobs en tant que plateforme d'orchestration unifiée au sein de l'écosystème Databricks.
• Vous apprendrez à concevoir et à mettre en œuvre des charges de travail de données à l'aide de graphes orientés acycliques (DAG), à configurer diverses options de planification et à implémenter des fonctionnalités avancées de workflow telles que l'exécution conditionnelle de tâches, les dépendances run-if et les boucles for each.
• Le cours couvre les meilleures pratiques pour créer des pipelines robustes et prêts pour la production, avec une sélection appropriée du compute, une orchestration modulaire, des techniques de gestion des erreurs et une conception tolérante aux pannes — le tout nativement intégré au sein de la Databricks Data Intelligence Platform.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33958","entityUrl":{"path":"/fr/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-french-6653"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-french-6653"}}],"nid":33958,"vid":254348,"title":"Building Databricks Apps with Genie Code and Lakebase - French","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps permet de créer et de déployer des applications de données et d'IA interactives directement sur la plateforme Databricks. Mais le développement assisté par IA ne se résume pas à la génération de code — il s'agit avant tout de développer un workflow efficace.
Dans ce cours pratique, vous construirez une application Databricks Apps s'appuyant sur Lakebase, de bout en bout, en utilisant Genie Code comme assistant de développement IA. Au fil du cours, vous apprendrez une approche pratique et reproductible du développement assisté par IA : spécifier clairement l'intention avant de générer du code, travailler par petits incréments vérifiables, exploiter des compétences Genie Code réutilisables, et considérer les résultats générés par l'IA comme des éléments à examiner et à affiner — et non à accepter sans réserve.
Vous créerez et déploierez une application Databricks Apps, provisionnerez et connecterez une base de données Lakebase comme magasin transactionnel, implémenterez des opérations CRUD, et utiliserez Genie Code pour accélérer les tâches de développement courantes. À l'issue du cours, vous disposerez non seulement d'une application fonctionnelle, mais également d'un cadre pratique pour collaborer efficacement avec l'IA sur de futurs projets software.
Remarque : Databricks Academy adopte progressivement un format basé sur des notebooks pour les sessions en classe dans l’environnement Databricks et cesse d’utiliser des présentations pour les cours. Vous pouvez accéder aux notebooks de cours dans l’environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33926","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6573"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6573"}}],"nid":33926,"vid":254186,"title":"Get Started with Databricks for Machine Learning - French","price":"0.00","duration":7200,"body":{"processed":"Dans ce cours, vous apprendrez les compétences de base qui vous permettront d'utiliser la Databricks Data Intelligence Platform pour effectuer un workflow de data science et de machine learning simple. Vous aurez un aperçu du workspace et vous apprendrez à travailler avec des Notebooks. Vous explorerez l'analyse exploratoire des données et l'ingénierie des caractéristiques, suivrez et gérerez des modèles avec MLflow, expérimenterez avec Databricks Genie Code, et déploierez un modèle avec Databricks Model Serving. Enfin, le cours rassemble ces compétences dans un laboratoire complet couvrant le processus de machine learning de bout en bout.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33927","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6574"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6574"}}],"nid":33927,"vid":254187,"title":"Get Started with Databricks for Machine Learning - French","price":"75.00","duration":10800,"body":{"processed":"Dans ce cours, vous apprendrez les compétences de base qui vous permettront d'utiliser la Databricks Data Intelligence Platform pour effectuer un workflow de data science et de machine learning simple. Vous aurez un aperçu du workspace et vous apprendrez à travailler avec des Notebooks. Vous explorerez l'analyse exploratoire des données et l'ingénierie des caractéristiques, suivrez et gérerez des modèles avec MLflow, expérimenterez avec Databricks Genie Code, et déploierez un modèle avec Databricks Model Serving. Enfin, le cours rassemble ces compétences dans un laboratoire complet couvrant le processus de machine learning de bout en bout.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33887","entityUrl":{"path":"/fr/training/catalog/get-started-with-ai-agents-on-databricks-french-6125"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-ai-agents-on-databricks-french-6125"}}],"nid":33887,"vid":253939,"title":"Get Started with AI Agents on Databricks - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours est une introduction aux agents IA, à leur rôle dans les applications IA modernes, et à la manière de créer des applications d'agents IA sur la plateforme Databricks. Vous apprendrez les principes des agents IA, en quoi ils diffèrent des systèmes IA traditionnels, et vous explorerez leurs composants clés. À travers des démonstrations interactives et des travaux pratiques, vous verrez comment créer, déployer et évaluer des agents IA sur Databricks en utilisant Databricks AI et Agent Bricks. À la fin de ce cours, vous comprendrez comment créer et déployer des agents IA à l'aide de la Databricks Data + AI Platform.
Remarque : Databricks Academy passe à un format basé sur des notebooks pour les sessions en classe dans l’environnement Databricks, et n’utilise plus de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l’environnement de laboratoire Vocareum.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33882","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-6579"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-6579"}}],"nid":33882,"vid":253932,"title":"Get Started with Databricks for Generative AI - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours offre une introduction pratique à la Databricks Data Intelligence Platform, en mettant l'accent sur ses composants et fonctionnalités clés pour la création et le déploiement de systèmes d'IA générative. Les participants apprendront comment Databricks facilite le développement de solutions d'IA générative évolutives et exploreront des outils tels que AI Search, le Cadre Agent et les capacités d'IA générative de MLflow pour le suivi et l'enregistrement des modèles. Ce cours comprend une expérience pratique dans la construction et l'évaluation de pipelines Retrieval-Augmented Generation (RAG), le déploiement d'agents d'IA générative, et l'utilisation de cadres d'évaluation pour optimiser la performance. À la fin du cours, les apprenants seront équipés des compétences nécessaires pour concevoir, déployer et surveiller des applications courantes d'IA générative sur la Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33883","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-6580"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-6580"}}],"nid":33883,"vid":253933,"title":"Get Started with Databricks for Generative AI - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours offre une introduction pratique à la Databricks Data Intelligence Platform, en mettant l'accent sur ses composants et fonctionnalités clés pour la création et le déploiement de systèmes d'IA générative. Les participants apprendront comment Databricks facilite le développement de solutions d'IA générative évolutives et exploreront des outils tels que AI Search, le Cadre Agent et les capacités d'IA générative de MLflow pour le suivi et l'enregistrement des modèles. Ce cours comprend une expérience pratique dans la construction et l'évaluation de pipelines Retrieval-Augmented Generation (RAG), le déploiement d'agents d'IA générative, et l'utilisation de cadres d'évaluation pour optimiser la performance. À la fin du cours, les apprenants seront équipés des compétences nécessaires pour concevoir, déployer et surveiller des applications courantes d'IA générative sur la Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33825","entityUrl":{"path":"/fr/training/catalog/apache-spark-programming-with-databricks-french-6458"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/apache-spark-programming-with-databricks-french-6458"}}],"nid":33825,"vid":253493,"title":"Apache Spark Programming with Databricks - French","price":"1500.00","duration":57600,"body":{"processed":"Ce cours d'introduction constitue un point de départ approprié pour apprendre le Data Engineering avec Databricks.
Ci-dessous, nous décrivons chacun des quatre modules de quatre heures inclus dans ce cours.
Remarque : pour les quatre modules suivants, Databricks Academy adopte progressivement un format basé sur des notebooks pour les sessions en salle de classe au sein de l'environnement Databricks, abandonnant l'utilisation de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de lab Vocareum.
Introduction to Apache Spark
Ce cours accessible aux débutants couvre les fondamentaux d'Apache Spark pour le traitement de données à grande échelle. Vous explorerez l'architecture distribuée de Spark, maîtriserez l'API DataFrame et apprendrez à lire, écrire et traiter des données avec Python. Grâce à des exercices pratiques, vous développerez les compétences nécessaires pour exécuter efficacement des transformations et des actions Spark.
Developing Applications with Apache Spark
Maîtrisez le traitement de données à grande échelle avec Apache Spark dans ce cours. Apprenez à construire des pipelines ETL efficaces, à effectuer des analyses de données avancées et à optimiser les transformations de données distribuées à l'aide de l'API DataFrame de Spark. Explorez le regroupement, l'agrégation, les jointures, les opérations sur les ensembles et les fonctions de fenêtrage. Travaillez avec des types de données complexes tels que les tableaux, les maps et les structs, tout en appliquant les meilleures pratiques d'optimisation des performances.
Stream Processing and Analysis with Apache Spark
Ce cours guide les apprenants sur la manière de développer des applications de traitement de stream évolutives et tolérantes aux pannes en utilisant l'API Spark Structured Streaming sur Databricks.
Monitoring and Optimizing Apache Spark Workloads on Databricks
Ce cours couvre les composants essentiels de la plateforme Databricks et Apache Spark avec Delta Lake, en mettant l'accent sur l'architecture Lakehouse, Unity Catalog et les techniques de Gestion des données telles que les Transactions ACID et la maintenance des tables. De plus, il enseigne aux étudiants comment Optimiser la performance des requêtes grâce au partitionnement, aux shuffles et aux outils de réglage, tout en utilisant le Spark UI pour surveiller les applications et résoudre les goulots d'étranglement.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33813","entityUrl":{"path":"/fr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-french-6556"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-french-6556"}}],"nid":33813,"vid":253351,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours couvre les composants essentiels de la plateforme Databricks et Apache Spark avec Delta Lake, en mettant l'accent sur l'architecture Lakehouse, Unity Catalog et les techniques de Gestion des données telles que les Transactions ACID et la maintenance des tables. De plus, il enseigne aux étudiants comment Optimiser la performance des requêtes grâce au partitionnement, aux shuffles et aux outils de réglage, tout en utilisant le Spark UI pour surveiller les applications et résoudre les goulots d'étranglement.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33807","entityUrl":{"path":"/fr/training/catalog/stream-processing-and-analysis-with-apache-spark-french-6547"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/stream-processing-and-analysis-with-apache-spark-french-6547"}}],"nid":33807,"vid":253322,"title":"Stream Processing and Analysis with Apache Spark - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours guide les apprenants sur la manière de développer des applications de traitement de stream évolutives et tolérantes aux pannes en utilisant l'API Spark Structured Streaming sur Databricks.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 |한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33336","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6514"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6514"}}],"nid":33336,"vid":252743,"title":"Get Started with Databricks: End to End - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours est une introduction complète et pratique à la Databricks Data Intelligence Platform. Vous suivrez un parcours unique de bout en bout qui commence dans le workspace et se termine par une introduction à l'IA et au machine learning, en couvrant les compétences quotidiennes dont vous avez besoin pour travailler avec des données sur Databricks.
Le cours couvre les sujets suivants :
À la fin de ce cours, vous serez à l'aise pour naviguer dans Databricks, trouver et gouverner des données dans Unity Catalog, écrire du SQL et du code dans des notebooks avec l'assistance de l'IA, créer des Tableaux de bord et explorer des données avec Génie.
Remarque : pour les fichiers de cours SCORM, veuillez fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d’être marqué comme terminé.
Languages Available : English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33337","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6515"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6515"}}],"nid":33337,"vid":252744,"title":"Get Started with Databricks: End to End - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours est une introduction complète et pratique à la Databricks Data Intelligence Platform. Vous suivrez un parcours unique de bout en bout qui commence dans le workspace et se termine par une introduction à l'IA et au machine learning, en couvrant les compétences quotidiennes dont vous avez besoin pour travailler avec des données sur Databricks.
Le cours couvre les sujets suivants :
À la fin de ce cours, vous serez à l'aise pour naviguer dans Databricks, trouver et gouverner des données dans Unity Catalog, écrire du SQL et du code dans des notebooks avec l'assistance de l'IA, créer des Tableaux de bord et explorer des données avec Génie.
Remarque : pour les fichiers de cours SCORM, veuillez fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d’être marqué comme terminé.
Languages Available : English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33347","entityUrl":{"path":"/fr/training/catalog/developing-applications-with-apache-spark-french-6532"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/developing-applications-with-apache-spark-french-6532"}}],"nid":33347,"vid":252754,"title":"Developing Applications with Apache Spark - French","price":"750.00","duration":14400,"body":{"processed":"Maîtrisez le traitement de données à grande échelle avec Apache Spark dans ce cours. Apprenez à construire des pipelines ETL efficaces, à effectuer des analyses de données avancées et à optimiser les transformations de données distribuées à l'aide de l'API DataFrame de Spark. Explorez le regroupement, l'agrégation, les jointures, les opérations sur les ensembles et les fonctions de fenêtrage. Travaillez avec des types de données complexes tels que les tableaux, les maps et les structs, tout en appliquant les meilleures pratiques d'optimisation des performances.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33331","entityUrl":{"path":"/fr/training/catalog/introduction-to-apache-spark-french-6461"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/introduction-to-apache-spark-french-6461"}}],"nid":33331,"vid":252719,"title":"Introduction to Apache Spark - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours accessible aux débutants couvre les fondamentaux d'Apache Spark pour le traitement de données à grande échelle. Vous explorerez l'architecture distribuée de Spark, maîtriserez l'API DataFrame et apprendrez à lire, écrire et traiter des données avec Python. Grâce à des exercices pratiques, vous développerez les compétences nécessaires pour exécuter efficacement des transformations et des actions Spark.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33323","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6491"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6491"}}],"nid":33323,"vid":252695,"title":"Get Started with Databricks Apps - French","price":"0.00","duration":3600,"body":{"processed":"Ce cours présente Databricks Apps, une fonctionnalité qui permet aux développeurs de créer et de déployer des applications de données et d'IA sécurisées directement sur la plateforme Databricks. Il est principalement destiné aux data scientists, aux ingénieurs de données et aux développeurs qui ont besoin de créer des applications personnalisées rendant les insights accessibles aux utilisateurs non techniques au sein de leurs organisations.
Le cours commence par fournir une vue d'ensemble des principaux composants de Databricks Apps, puis aborde le déploiement d'applications simples s'intégrant à un service externe ainsi qu'à une ressource Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33324","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6496"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6496"}}],"nid":33324,"vid":252696,"title":"Get Started with Databricks Apps - French","price":"75.00","duration":7200,"body":{"processed":"Ce cours présente Databricks Apps, une fonctionnalité qui permet aux développeurs de créer et de déployer des applications de données et d'IA sécurisées directement sur la plateforme Databricks. Il est principalement destiné aux data scientists, aux ingénieurs de données et aux développeurs qui ont besoin de créer des applications personnalisées rendant les insights accessibles aux utilisateurs non techniques au sein de leurs organisations.
Le cours commence par fournir une vue d'ensemble des principaux composants de Databricks Apps, puis aborde le déploiement d'applications simples s'intégrant à un service externe ainsi qu'à une ressource Databricks.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32114","entityUrl":{"path":"/fr/training/catalog/ai-agent-fundamentals-accreditation-french-6480"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/ai-agent-fundamentals-accreditation-french-6480"}}],"nid":32114,"vid":251041,"title":"AI Agent Fundamentals Accreditation - French","price":"0.00","duration":1800,"body":{"processed":"Bienvenue dans le quiz d’accréditation AI Agent Fundamentals. Dans ce quiz de 20 questions, nous évaluerons vos connaissances sur les fondamentaux des AI agents, leurs applications en entreprise, ainsi que la manière de les créer et de les déployer avec Mosaic AI et Agent Bricks de Databricks. Si vous réussissez ce quiz, un badge vous sera attribué (sous 48 heures) via notre prestataire de badges, Accredible. Bonne chance !
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32082","entityUrl":{"path":"/fr/training/catalog/databricks-fundamentals-french-3715"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/databricks-fundamentals-french-3715"}}],"nid":32082,"vid":250710,"title":"Databricks Fundamentals - French","price":"0.00","duration":3600,"body":{"processed":"Ce cours est une introduction fondamentale à Databricks et à la Databricks Platform. Vous découvrirez les problèmes auxquels font face les équipes modernes spécialisées dans les données et l'IA, le concept de lakehouse au cœur de la plateforme, les produits et fonctionnalités qu'elle propose, la manière dont elle garantit la fiabilité des données et de l'IA grâce à une gouvernance unifiée, ainsi qu'une visite guidée du workspace.
Ces vidéos sont proposées dans un ordre suggéré, mais vous êtes libre de les visionner dans l'ordre de votre choix. De plus, nous vous recommandons de regarder l'intégralité du contenu vidéo disponible avant de tenter l'évaluation d'accréditation Databricks Fundamentals.
Aucune connaissance technique préalable de Databricks ou des plateformes de données n'est requise.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32061","entityUrl":{"path":"/fr/training/catalog/machine-learning-with-databricks-french-6476"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/machine-learning-with-databricks-french-6476"}}],"nid":32061,"vid":250410,"title":"Machine Learning with Databricks - French","price":"1500.00","duration":57600,"body":{"processed":"Bienvenue dans Machine Learning with Databricks !
Ce cours est votre porte d'entrée vers la maîtrise des workflows de machine learning sur Databricks. Plongez dans la préparation des données, le développement de modèles, le déploiement et les opérations, guidé par des instructeurs experts. Apprenez les compétences essentielles pour l'exploration des données, l'entraînement des modèles et les stratégies de déploiement adaptées à Databricks. À la fin du cours, vous disposerez des connaissances et de la confiance nécessaires pour naviguer dans l'ensemble du cycle de vie du machine learning sur la plateforme Databricks, ce qui vous permettra de créer et de déployer efficacement des solutions de machine learning robustes.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Data Preparation for Machine Learning
Ce cours se concentre sur les fondamentaux de la préparation des données pour le machine learning avec Databricks. Les participants acquerront les compétences essentielles pour explorer, nettoyer et organiser les données en vue d'applications de machine learning traditionnelles. Les sujets clés comprennent la visualisation des données, l'Ingénierie des caractéristiques et les stratégies optimales de stockage des fonctionnalités. Grâce à des exercices pratiques, les participants acquerront une expérience concrète dans la préparation efficace de jeux de données pour le machine learning au sein de Databricks. Ce cours est conçu pour les data scientists de niveau associé et les praticiens du machine learning, ainsi que pour les personnes souhaitant renforcer leurs compétences en préparation des données, garantissant ainsi une base solide pour le déploiement Réussi d'un Modèle de machine learning.
Machine Learning Model Development
Ce cours complet offre un guide pratique pour développer des modèles de machine learning traditionnels sur Databricks, en mettant l'accent sur des démonstrations pratiques et des workflows utilisant les bibliothèques de ML les plus courantes. Les participants exploreront des techniques de ML essentielles, notamment la régression et le clustering, tout en tirant parti des puissantes capacités de Databricks. Le cours couvre l'intégration de MLflow pour le suivi des modèles, le Databricks Feature Store pour la gestion des features, et Optuna pour l'optimisation des hyperparamètres. Les participants apprendront en outre à accélérer le développement de modèles avec Genie Code, l'assistant de codage IA de Databricks qui utilise le langage naturel, des connexions MCP, des instructions et des compétences pour guider l'ensemble du cycle de vie du ML. À la fin du cours, les apprenants disposeront de compétences pratiques et concrètes pour développer, optimiser et déployer efficacement des modèles de machine learning dans l'environnement Databricks.
Machine Learning Model Deployment
Ce cours est conçu pour présenter trois stratégies principales de déploiement de machine learning et illustrer la mise en œuvre de chacune de ces stratégies sur Databricks. Après une exploration des fondamentaux du déploiement de modèles, le cours aborde le batch inference, en proposant des démonstrations pratiques et des travaux dirigés pour l'utilisation d'un modèle dans des scénarios de batch inference, ainsi que des considérations relatives à l'optimisation des performance. La deuxième partie du cours couvre de manière exhaustive le déploiement de pipeline, tandis que le dernier segment se concentre sur le déploiement en temps réel. Les participants s'engageront dans des démonstrations pratiques et des travaux dirigés, en déployant des modèles avec Model Serving et en utilisant le serving endpoint pour l'inférence en temps réel.
Machine Learning Operations
Ce cours guidera les participants à travers une exploration complète des opérations de Modèle de machine learning, en mettant l'accent sur le MLOps et la gestion du cycle de vie des modèles. La première partie couvre les composants essentiels du MLOps et les meilleures pratiques, offrant aux participants une base solide pour opérationnaliser efficacement les Modèles de machine learning. Dans la seconde partie du cours, nous aborderons les fondamentaux du cycle de vie des modèles, en démontrant comment le parcourir de manière fluide en utilisant le Model Registry conjointement avec Unity Catalog pour une gestion efficace des modèles. À la conclusion du cours, les participants auront acquis des DNT pratiques ainsi qu'une compréhension approfondie des principes du MLOps, dotés des compétences nécessaires pour naviguer dans le paysage complexe des opérations de Modèle de machine learning.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"32058","entityUrl":{"path":"/fr/training/catalog/ai-agent-fundamentals-french-6482"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/ai-agent-fundamentals-french-6482"}}],"nid":32058,"vid":250388,"title":"AI Agent Fundamentals - French","price":"0.00","duration":5400,"body":{"processed":"Ce cours fondamental présente les agents IA et leur utilisation dans les applications d'entreprise sur Databricks, notamment la plateforme Mosaic AI et Agent Bricks. Les apprenants examineront ce que sont les agents IA, comment ils fonctionnent et comment ils imitent le raisonnement humain pour traiter des tâches complexes.
Le cours aborde des cas d'utilisation concrets d'agents et fournit une introduction de base à des sujets avancés tels que les workflows agentiques et les systèmes multi-agents. Il explore également comment Agent Bricks simplifie le développement d'agents prêts pour l'entreprise dans diverses applications, avec des démonstrations montrant comment créer et utiliser des agents sur Databricks.
Remarque : pour les fichiers de cours SCORM, fermez la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela peut empêcher le module SCORM d’être marqué comme terminé.
Languages Available: English | 日本語 | Português BR | 한국어
L'IA générative est passée du stade d'expérience émergente à celui de capacité essentielle pour l'entreprise, alimentant tout, des services d'assistance client intelligents aux agents IA qui automatisent des workflows complexes.
Les organisations qui savent comment la déployer efficacement — en s'appuyant sur leurs propres données et en la gouvernant pour instaurer la confiance — seront celles qui donneront le rythme dans leurs industries. Mais avec de nouveaux modèles publiés chaque semaine et des capacités en évolution rapide, savoir comment évaluer et appliquer le GenAI de manière stratégique importe davantage que de courir après la dernière version. Mettez-vous à niveau sur les fondamentaux de l'IA générative — ce qu'elle peut faire, où elle apporte une réelle valeur commerciale, et comment la mettre en œuvre de manière sécurisée sur Databricks — grâce à cette formation à la demande gratuite.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32037","entityUrl":{"path":"/fr/training/catalog/data-governance-at-scale-french-6429"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-governance-at-scale-french-6429"}}],"nid":32037,"vid":250210,"title":"Data Governance at Scale - French","price":"750.00","duration":14400,"body":{"processed":"Dans ce cours, vous apprendrez à implémenter la Gouvernance des données à grande échelle sur Databricks à l'aide de Unity Catalog, en mettant l'accent sur le contrôle d'accès basé sur les attributs, l'observabilité et le partage fédéré. Vous configurerez l'ABAC avec des tags gouvernés, migrerez depuis des contrôles affinés hérités, activerez et utiliserez les tables système pour l'audit et le monitoring des coûts, déploierez le monitoring de la qualité des données pour la qualité des données et des modèles, interpréterez la traçabilité des données pour l'impact et la conformité, et appliquerez la gouvernance fédérée et les modèles Delta Sharing pour une collaboration sécurisée entre clouds.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31909","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6445"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6445"}}],"nid":31909,"vid":249972,"title":"Get Started with Databricks for Data Warehousing - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours offre une vue d'ensemble complète et pratique de l'approche moderne de Databricks en matière de data warehousing, en mettant en évidence la manière dont une architecture data lakehouse combine les atouts des entrepôts de données traditionnels avec la flexibilité et l'évolutivité du cloud. En travaillant de bout en bout avec un détaillant fictif (Vintage Audio Co.), vous allez Explorer le workspace, exécuter des requêtes sur des tables Unity Catalog gouvernées, maintenir les performances des tables gérées par Unity Catalog pour les lectures analytiques, charger des données de manière incrémentielle avec Auto Loader, modéliser un schéma en étoile et fournir des insights cohérents via les vues de métriques Unity Catalog — le tout depuis un environnement unique et gouverné, avec des fonctionnalités pilotées par l'IA (Predictive Optimization, Génie Code) intégrées tout au long du parcours.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31910","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6446"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6446"}}],"nid":31910,"vid":249973,"title":"Get Started with Databricks for Data Warehousing - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours offre une vue d'ensemble complète et pratique de l'approche moderne de Databricks en matière de data warehousing, en mettant en évidence la manière dont une architecture data lakehouse combine les atouts des entrepôts de données traditionnels avec la flexibilité et l'évolutivité du cloud. En travaillant de bout en bout avec un détaillant fictif (Vintage Audio Co.), vous allez Explorer le workspace, exécuter des requêtes sur des tables Unity Catalog gouvernées, maintenir les performances des tables gérées par Unity Catalog pour les lectures analytiques, charger des données de manière incrémentielle avec Auto Loader, modéliser un schéma en étoile et fournir des insights cohérents via les vues de métriques Unity Catalog — le tout depuis un environnement unique et gouverné, avec des fonctionnalités pilotées par l'IA (Predictive Optimization, Génie Code) intégrées tout au long du parcours.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31871","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6404"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-end-to-end-french-6404"}}],"nid":31871,"vid":249485,"title":"Get Started with Databricks: End to End - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours est une introduction complète et pratique à la Databricks Data Intelligence Platform. Vous suivrez un parcours unique de bout en bout qui commence dans le workspace et se termine par une introduction à l'IA et au machine learning, en couvrant les compétences quotidiennes dont vous avez besoin pour travailler avec des données sur Databricks.
Le cours couvre les sujets suivants :
• La navigation dans le workspace Databricks, les options de compute et les expériences Lakehouse et Génie.
• La compréhension et l'ingestion de données avec Unity Catalog, notamment l'upload de fichiers et l'Explorateur de catalogues.
• Le travail dans les Notebooks Databricks et l'utilisation de Genie Code pour écrire et déboguer du code.
• L'interrogation de données avec SQL, la gestion des requêtes sauvegardées, ainsi que la création de Tableaux de bord et de visualisations.
• L'exploration de données en langage naturel avec les agents Génie.
• Une introduction à l'IA et au machine learning avec MLflow et l'agent Data Science.
À la fin de ce cours, vous serez à l'aise pour naviguer dans Databricks, trouver et gouverner des données dans Unity Catalog, écrire du SQL et du code dans des notebooks avec l'assistance de l'IA, créer des Tableaux de bord et explorer des données avec Génie.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31814","entityUrl":{"path":"/fr/training/catalog/machine-learning-operations-french-6376"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/machine-learning-operations-french-6376"}}],"nid":31814,"vid":248668,"title":"Machine Learning Operations - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours guidera les participants à travers une exploration complète des opérations de Modèle de machine learning, en mettant l'accent sur le MLOps et la gestion du cycle de vie des modèles. La première partie couvre les composants essentiels du MLOps et les meilleures pratiques, offrant aux participants une base solide pour opérationnaliser efficacement les Modèles de machine learning. Dans la seconde partie du cours, nous aborderons les fondamentaux du cycle de vie des modèles, en démontrant comment le parcourir de manière fluide en utilisant le Model Registry conjointement avec Unity Catalog pour une gestion efficace des modèles. À la conclusion du cours, les participants auront acquis des DNT pratiques ainsi qu'une compréhension approfondie des principes du MLOps, dotés des compétences nécessaires pour naviguer dans le paysage complexe des opérations de Modèle de machine learning.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31801","entityUrl":{"path":"/fr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-french-6374"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-french-6374"}}],"nid":31801,"vid":248570,"title":"Get Started with SQL Analytics and BI on Databricks - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente la Databricks Data Intelligence Platform et les compétences fondamentales dont un analyste de données a besoin pour ses activités quotidiennes d'analyse de données SQL et de BI. Vous apprendrez à naviguer dans le workspace et Unity Catalog, à écrire des requêtes SQL sur des tables gérées par Unity Catalog depuis un Serverless SQL Warehouse, à utiliser Genie Code pour générer et déboguer du SQL, à travailler avec Delta Lake (DML, historique des versions, time travel et restauration), à créer et publier des Tableaux de bord IA/BI, et à créer des Génie Agents pour l'analyse de données conversationnelle.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31334","entityUrl":{"path":"/fr/training/catalog/data-modeling-strategies-french-6306"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-modeling-strategies-french-6306"}}],"nid":31334,"vid":246929,"title":"Data Modeling Strategies - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours guide les praticiens à travers l'ensemble des approches de modélisation des données sur la Databricks Data Intelligence Platform - des techniques classiques de data warehouse (Inmon, Kimball, Data Vault 2.0), en passant par les cas d'usage ML pilotés par le Feature Store, jusqu'à la mise en production des données via des Produits de données sur Unity Catalog.
Chaque approche de modélisation est introduite par un exposé, puis consolidée par une démonstration pratique sur un ensemble de données partagé (échantillons TPC-H). Le cours se termine par un laboratoire complet de bout en bout couvrant la modélisation ERM, la modélisation dimensionnelle, Data Vault 2.0 et le Feature Store dans un workflow intégré unique.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31095","entityUrl":{"path":"/fr/training/catalog/machine-learning-model-deployment-french-6290"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/machine-learning-model-deployment-french-6290"}}],"nid":31095,"vid":246474,"title":"Machine Learning Model Deployment - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours est conçu pour présenter trois stratégies principales de déploiement de machine learning et illustrer la mise en œuvre de chacune de ces stratégies sur Databricks. Après une exploration des fondamentaux du déploiement de modèles, le cours aborde le batch inference, en proposant des démonstrations pratiques et des travaux dirigés pour l'utilisation d'un modèle dans des scénarios de batch inference, ainsi que des considérations relatives à l'optimisation des performance. La deuxième partie du cours couvre de manière exhaustive le déploiement de pipeline, tandis que le dernier segment se concentre sur le déploiement en temps réel. Les participants s'engageront dans des démonstrations pratiques et des travaux dirigés, en déployant des modèles avec Model Serving et en utilisant le serving endpoint pour l'inférence en temps réel.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31086","entityUrl":{"path":"/fr/training/catalog/data-preparation-for-machine-learning-french-6283"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-preparation-for-machine-learning-french-6283"}}],"nid":31086,"vid":246448,"title":"Data Preparation for Machine Learning - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours se concentre sur les fondamentaux de la préparation des données pour le machine learning avec Databricks. Les participants acquerront les compétences essentielles pour explorer, nettoyer et organiser les données en vue d'applications de machine learning traditionnelles. Les sujets clés comprennent la visualisation des données, l'Ingénierie des caractéristiques et les stratégies optimales de stockage des fonctionnalités. Grâce à des exercices pratiques, les participants acquerront une expérience concrète dans la préparation efficace de jeux de données pour le machine learning au sein de Databricks. Ce cours est conçu pour les data scientists de niveau associé et les praticiens du machine learning, ainsi que pour les personnes souhaitant renforcer leurs compétences en préparation des données, garantissant ainsi une base solide pour le déploiement Réussi d'un Modèle de machine learning.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31052","entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-6067"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-6067"}}],"nid":31052,"vid":246149,"title":"Building Agentic Applications on Databricks - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours enseigne aux étudiants comment créer des applications agentiques de niveau production sur Databricks. Les étudiants apprennent à créer des outils d’agent gouvernés avec Unity Catalog et MCP, à construire des systèmes mono-agent et multi-agents avec le OpenAI Agents SDK, et à tirer parti d’Agent Bricks et de Genie pour des cas d’usage de knowledge assistant orchestrés par un agent supervisor. Le cours couvre l’ensemble du parcours, du prototypage d’outils au déploiement en production, avec une pratique du tracing MLflow pour observer l’exécution des agents.
Remarque : Pour les fichiers de cours SCORM, veuillez vous assurer de fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Leçon suivante », car cela pourrait empêcher le module SCORM d’être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31053","entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-6068"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-6068"}}],"nid":31053,"vid":246150,"title":"Building Agentic Applications on Databricks - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours enseigne aux étudiants comment créer des applications agentiques de niveau production sur Databricks. Les étudiants apprennent à créer des outils d’agent gouvernés avec Unity Catalog et MCP, à construire des systèmes mono-agent et multi-agents avec le OpenAI Agents SDK, et à tirer parti d’Agent Bricks et de Genie pour des cas d’usage de knowledge assistant orchestrés par un agent supervisor. Le cours couvre l’ensemble du parcours, du prototypage d’outils au déploiement en production, avec une pratique du tracing MLflow pour observer l’exécution des agents.
Remarque : Pour les fichiers de cours SCORM, veuillez vous assurer de fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Leçon suivante », car cela pourrait empêcher le module SCORM d’être marqué comme terminé.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31029","entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-6260"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-6260"}}],"nid":31029,"vid":246061,"title":"SQL Programming and Procedural Logic - French","price":"0.00","duration":7200,"body":{"processed":"Dans ce cours, vous explorerez les compétences essentielles en programmation SQL et logique procédurale dans Databricks, en vous concentrant sur la création de flux de travail analytiques modulaires, maintenables et prêts pour la production. Vous commencerez par découvrir les constructions SQL clés — telles que les Common Table Expressions (y compris les CTE récursives avancées), les objets à portée de session comme les vues et tables temporaires, et les User Defined Functions — qui rendent votre développement SQL plus propre et réutilisable. Le cours vous guide ensuite à travers des techniques avancées de scripting SQL à l'aide d'instructions composées, de variables, de flux de contrôle, de conditions, de boucles et d'une gestion robuste des erreurs pour créer des processus SQL structurés et flexibles. Vous apprendrez également à garantir la cohérence des données dans ces pipelines en plusieurs étapes grâce à des transactions multi-instructions conformes ACID. Enfin, vous découvrirez comment encapsuler la logique dans des SQL Stored Procedures et orchestrer des flux de travail complexes avec Lakeflow Jobs et des stratégies de migration, transformant les tâches héritées en pipelines modulaires et automatisés qui exploitent toutes les capacités de la plateforme Databricks.
Remarque : pour les fichiers de cours SCORM, fermez la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela peut empêcher le module SCORM d’être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31030","entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-6261"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-6261"}}],"nid":31030,"vid":246062,"title":"SQL Programming and Procedural Logic - French","price":"75.00","duration":10800,"body":{"processed":"Dans ce cours, vous explorerez les compétences essentielles en programmation SQL et logique procédurale dans Databricks, en vous concentrant sur la création de flux de travail analytiques modulaires, maintenables et prêts pour la production. Vous commencerez par découvrir les constructions SQL clés — telles que les Common Table Expressions (y compris les CTE récursives avancées), les objets à portée de session comme les vues et tables temporaires, et les User Defined Functions — qui rendent votre développement SQL plus propre et réutilisable. Le cours vous guide ensuite à travers des techniques avancées de scripting SQL à l'aide d'instructions composées, de variables, de flux de contrôle, de conditions, de boucles et d'une gestion robuste des erreurs pour créer des processus SQL structurés et flexibles. Vous apprendrez également à garantir la cohérence des données dans ces pipelines en plusieurs étapes grâce à des transactions multi-instructions conformes ACID. Enfin, vous découvrirez comment encapsuler la logique dans des SQL Stored Procedures et orchestrer des flux de travail complexes avec Lakeflow Jobs et des stratégies de migration, transformant les tâches héritées en pipelines modulaires et automatisés qui exploitent toutes les capacités de la plateforme Databricks.
Remarque : pour les fichiers de cours SCORM, fermez la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela peut empêcher le module SCORM d’être marqué comme terminé.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30896","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6204"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-apps-french-6204"}}],"nid":30896,"vid":245356,"title":"Get Started with Databricks Apps - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente Databricks Apps, une fonctionnalité qui permet aux développeurs de créer et de déployer des applications de données et d'IA sécurisées directement sur la plateforme Databricks. Il est principalement destiné aux data scientists, aux ingénieurs de données et aux développeurs qui ont besoin de créer des applications personnalisées rendant les insights accessibles aux utilisateurs non techniques au sein de leurs organisations.
Le cours commence par fournir une vue d'ensemble des principaux composants de Databricks Apps, puis aborde le déploiement d'applications simples s'intégrant à un service externe ainsi qu'à une ressource Databricks.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"30889","entityUrl":{"path":"/fr/training/catalog/automated-deployment-with-declarative-automation-bundles-french-6215"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/automated-deployment-with-declarative-automation-bundles-french-6215"}}],"nid":30889,"vid":245296,"title":"Automated Deployment with Declarative Automation Bundles - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours propose une revue approfondie des principes DevOps et de leur application aux projets Databricks. Il commence par un aperçu des concepts fondamentaux de DevOps, DataOps, intégration continue (CI), déploiement continu (CD) et tests, et explore comment ces principes peuvent s'appliquer aux pipelines d'ingénierie des données.
Le cours se concentre ensuite sur le déploiement continu au sein du processus CI/CD, en examinant des outils tels que l'API REST, le SDK et le CLI Databricks pour le déploiement de projets. Vous découvrirez les Declarative Automation Bundles (DABs) et leur place dans le processus CI/CD. Vous approfondirez leurs composants clés, la structure des dossiers et la façon dont ils accélèrent le déploiement dans divers environnements cibles sur Databricks. Vous apprendrez également à ajouter des variables, modifier, valider, déployer et exécuter des Declarative Automation Bundles pour plusieurs environnements avec différentes configurations via le CLI Databricks.
Enfin, le cours présente Visual Studio Code comme environnement de développement interactif (IDE) pour construire, tester et déployer des Declarative Automation Bundles localement, en optimisant le processus de développement. Le cours se termine par une introduction à l'automatisation des pipelines de déploiement avec GitHub Actions afin d'améliorer le flux de travail CI/CD avec les Declarative Automation Bundles.
À la fin de ce cours, vous serez prêt à automatiser les déploiements de projets Databricks avec les Declarative Automation Bundles, en améliorant l'efficacité grâce aux pratiques DevOps.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30879","entityUrl":{"path":"/fr/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-french-6185"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-french-6185"}}],"nid":30879,"vid":245134,"title":"Advanced Techniques with Apache Spark Declarative Pipelines - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours explore les Pipeline déclaratifs Apache Spark (SDP) de Databricks pour la création de pipelines streaming de qualité production. Vous apprendrez des modèles de conception avancés, une application robuste de la qualité des données et une intégration multiplateforme essentiels pour l'ingénierie lakehouse en conditions réelles.
Tout au long du cours, vous plongerez dans les techniques modernes d'Ingestion de données et de traitement, en maîtrisant des outils tels que le clustering liquide pour l'optimisation de la Disposition et le modèle de streaming Multiplex pour les événements à schémas mixtes. À la fin des modules, vous saurez gérer en toute confiance l'évolution du schéma, automatiser le change data capture (CDC) et garantir l'Intégrité des données.
À travers des cours magistraux et des démonstrations pratiques, vous allez:
• Construire des pipelines multi-flux pour ingérer des données multi-sources dans une table Bronze unifiée.
• Appliquer le clustering liquide et les attentes de qualité des données sur les couches Argent et gold.
• Implémenter le modèle Multiplex avec Iceberg UniForm pour un accès aux données multiplateforme.
• Automatiser le suivi de l'historique SCD de type 2 à l'aide d'AUTO CDC INTO.
• Concevoir des pipelines de quarantaine sans perte de données pour auditer et gérer les enregistrements non valides.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30850","entityUrl":{"path":"/fr/training/catalog/building-rag-agents-with-agent-bricks-french-6042"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-rag-agents-with-agent-bricks-french-6042"}}],"nid":30850,"vid":244643,"title":"Building RAG Agents with Agent Bricks - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours propose une formation pratique pour créer des agents de récupération avec Databricks Agent Bricks. Les participants apprendront à explorer et interroger des Knowledge Assistants, à transformer des documents non structurés en données structurées avec les AI Functions, à découper le texte pour la récupération sémantique, à créer des index AI Search, et à concevoir des Knowledge Assistants prêts pour la production s’appuyant sur plusieurs sources de connaissances.
Remarque : Pour les fichiers de cours SCORM, veuillez vous assurer de fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Leçon suivante », car cela pourrait empêcher le module SCORM d’être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30843","entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5882"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5882"}}],"nid":30843,"vid":244570,"title":"Get Started with Lakebase - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours de démarrage présente Databricks Lakebase, un service PostgreSQL Entièrement géré intégré à la Databricks Data Intelligence Platform, qui rapproche les charges de travail opérationnelles (OLTP) et analytiques (OLAP).
Le cours débute par un exposé conceptuel comparant les systèmes OLTP et OLAP, en expliquant leurs caractéristiques de performance respectives, leurs modèles de stockage et leurs cas d'usage typiques. Vous explorerez également les défis auxquels font face les organisations qui maintiennent des bases de données transactionnelles et des plateformes d'analyse de données séparées, notamment en matière de déplacement des données, de latence et de complexité architecturale.
Vous découvrirez ensuite comment Databricks Lakebase contribue à relever ces défis en fournissant une base de données opérationnelle compatible PostgreSQL qui s'intègre directement au Databricks Lakehouse, permettant ainsi aux applications opérationnelles et à l'analyse de données de fonctionner ensemble au sein d'une plateforme unifiée.
À travers des travaux pratiques, vous allez:
Créer et Explorer un projet Lakebase en utilisant un compute à mise à l'échelle automatique
• Naviguer dans l'interface utilisateur de Lakebase, notamment les fonctionnalités de branchement, de monitoring et les paramètres de configuration
• Créer des tables et les interroger à l'aide de l'éditeur SQL de Lakebase
• Interroger les données Lakebase depuis Databricks en utilisant Lakehouse Federation et des catalogues étrangers
• Effectuer un Reverse ETL en synchronisant des tables Delta vers Lakebase
• Se connecter à Lakebase depuis Python et effectuer des opérations CRUD de base
Il s'agit d'un cours de démarrage ; l'accent est donc mis sur la compréhension des concepts fondamentaux et des flux de travail de base pour travailler avec Lakebase. La création d'applications de production complètes sur Lakebase dépasse le cadre de ce cours.
À l'issue du cours, vous comprendrez comment Lakebase permet aux organisations de rapprocher les systèmes opérationnels et l'analyse de données au sein d'une plateforme unique et gouvernée, propulsée par Unity Catalog et le Databricks Lakehouse.
Remarque : pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30823","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-platform-administration-french-6153"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-platform-administration-french-6153"}}],"nid":30823,"vid":244450,"title":"Get Started with Databricks Platform Administration - French","price":"0.00","duration":7200,"body":{"processed":"Dans ce cours, vous apprendrez les bases de l'administration de la plateforme sur le Databricks Data Intelligence Platform. Il offre une vue d'ensemble complète de Unity Catalog, un composant essentiel pour une Gouvernance des données efficace dans les environnements Databricks. Divisé en cinq modules, il commence par une introduction détaillée à l'infrastructure Databricks et à sa Plateforme d'intelligence des données, incluant une présentation approfondie du Databricks Workspace. Vous explorerez les principes de Gouvernance des données au sein de Unity Catalog, en couvrant ses concepts clés, son architecture et ses rôles. Le cours met également l'accent sur la gestion des métastores Unity Catalog et des ressources compute, notamment les clusters et les entrepôts SQL. Enfin, vous maîtriserez le contrôle d'accès aux données en apprenant les privilèges, les accès affinés et la manière de gouverner les objets de données. À l'issue de ce cours, vous disposerez des compétences essentielles pour administrer Unity Catalog afin de mettre en œuvre une Gouvernance des données efficace, Optimiser les ressources compute et appliquer des stratégies robustes de sécurité des données. Avec l'achat d'un abonnement Databricks Labs, le cours se conclut également par un exercice de laboratoire complet permettant de mettre en pratique ce que vous avez appris dans un environnement Databricks Workspace en conditions réelles.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30762","entityUrl":{"path":"/fr/training/catalog/get-started-with-data-governance-on-databricks-french-6139"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-data-governance-on-databricks-french-6139"}}],"nid":30762,"vid":243148,"title":"Get Started with Data Governance on Databricks - French","price":"0.00","duration":7200,"body":{"processed":"Dans ce cours, vous allez explorer Unity Catalog et les contrôles d'accès granulaires sur Databricks à travers des démonstrations pratiques et un laboratoire récapitulatif. Vous découvrirez les types de Table, la configuration du Catalogue et des schémas, la gestion des accès basée sur les groupes, ainsi que les stratégies de migration des contrôles d'accès. Le cours comprend des démonstrations sur l'application des contrôles d'accès granulaires avec la sécurité au niveau des lignes et le masquage des colonnes, le contrôle d'accès basé sur les attributs, la combinaison des contrôles, la migration des contrôles, ainsi qu'un laboratoire pour une mise en œuvre complète de la gouvernance.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30721","entityUrl":{"path":"/fr/training/catalog/introduction-to-python-for-data-science-and-data-engineering-french-6116"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/introduction-to-python-for-data-science-and-data-engineering-french-6116"}}],"nid":30721,"vid":241315,"title":"Introduction to Python for Data Science and Data Engineering - French","price":"1500.00","duration":57600,"body":{"processed":"Ce cours est destiné aux débutants complets en Python afin de fournir les bases de l'interaction programmatique avec les données. Le cours commence par une introduction aux expressions de programmation, aux variables et aux types de données. Il aborde ensuite les instructions conditionnelles et de contrôle, les fonctions, les types Collection, les boucles, la gestion des erreurs et les classes. Vous apprendrez à étendre Python avec des bibliothèques externes et acquerrez de l'expérience dans l'utilisation de la bibliothèque Pandas pour l'analyse et la visualisation de données, notamment en faisant évoluer les Workflows Pandas avec Apache Spark. Enfin, vous explorerez les fondamentaux du cloud computing. Tout au long du cours, vous acquerrez une pratique concrète grâce à des exercices de laboratoire, avec des ressources supplémentaires pour approfondir vos connaissances en programmation après la formation.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.\n
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30644","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6098"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-machine-learning-french-6098"}}],"nid":30644,"vid":238903,"title":"Get Started with Databricks for Machine Learning - French","price":"0.00","duration":7200,"body":{"processed":"Dans ce cours, vous développerez les compétences fondamentales nécessaires pour utiliser la Databricks Data Intelligence Platform afin d'exécuter des workflows de machine learning et de prendre en charge des charges de travail de data science. Vous explorerez la plateforme du point de vue d'un praticien du machine learning, en abordant des sujets tels que la création et la gestion de fonctionnalités avec Feature Engineering dans Unity Catalog, la gestion du cycle de vie des modèles de bout en bout avec MLflow, et l'orchestration de pipeline avec Lakeflow Jobs. De plus, vous découvrirez l'inférence de modèles en temps réel avec Databricks Model Serving et vivrez l'approche transparente et conversationnelle de Databricks pour le développement de modèles grâce à Genie Code - Data Science Agent Mode, où vous utilisez des invites en langage naturel pour générer, exécuter et affiner de manière itérative des workflows de ML exécutables directement dans votre notebook. Le cours comprend des démonstrations animées par un instructeur, aboutissant à un laboratoire complet qui renforce les concepts abordés tout au long de la formation.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30615","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6080"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-warehousing-french-6080"}}],"nid":30615,"vid":238741,"title":"Get Started with Databricks for Data Warehousing - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours offre une vue d'ensemble complète et pratique de l'approche moderne de Databricks en matière de data warehousing, en mettant en évidence la manière dont une architecture data lakehouse combine les atouts des entrepôts de données traditionnels avec la flexibilité et l'évolutivité du cloud. En travaillant de bout en bout avec un détaillant fictif (Vintage Audio Co.), vous allez Explorer le workspace, exécuter des requêtes sur des tables Unity Catalog gouvernées, maintenir les performances des tables gérées par Unity Catalog pour les lectures analytiques, charger des données de manière incrémentielle avec Auto Loader, modéliser un schéma en étoile et fournir des insights cohérents via les vues de métriques Unity Catalog — le tout depuis un environnement unique et gouverné, avec des fonctionnalités pilotées par l'IA (Predictive Optimization, Génie Code) intégrées tout au long du parcours.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30617","entityUrl":{"path":"/fr/training/catalog/lakehouse-architecture-fundamentals-french-6087"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/lakehouse-architecture-fundamentals-french-6087"}}],"nid":30617,"vid":238743,"title":"Lakehouse Architecture Fundamentals - French","price":"0.00","duration":3600,"body":{"processed":"Un cours conceptuel basé sur The Data Lakehouse For Dummies. Il permet aux apprenants de passer de « je ne sais pas vraiment ce qu'est un lakehouse » à la capacité de tenir une conversation opérationnelle sur l'architecture lakehouse et les technologies qui la sous-tendent : les limites des architectures héritées, ce qu'est le lakehouse, ses technologies fondamentales, et la façon dont il permet le data intelligence et les charges de travail unifiées sur Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30444","entityUrl":{"path":"/fr/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-french-6045"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-french-6045"}}],"nid":30444,"vid":237601,"title":"Building Semantic Models in Databricks with UC Metric Views - French","price":"750.00","duration":14400,"body":{"processed":"Dans ce cours, vous apprendrez à permettre à vos consommateurs de données d'obtenir des insights métier validés en réduisant la charge de travail qui vous incombe, ainsi qu'au reste de l'équipe données et IA de votre entreprise. En construisant une couche sémantique au-dessus de votre couche gold, vous offrirez aux décideurs et aux analystes métier la possibilité d'explorer des indicateurs clés de performance métier de manière inédite, tout en maintenant des opérations sur les données efficaces et des métriques validées par l'entreprise.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30417","entityUrl":{"path":"/fr/training/catalog/answering-business-questions-with-databricks-genie-french-6021"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/answering-business-questions-with-databricks-genie-french-6021"}}],"nid":30417,"vid":237401,"title":"Answering Business Questions with Databricks Genie - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente Databricks Genie, un outil d'analyse de données conversationnelle qui vous permet de poser des questions en langage clair sur les données de votre organisation et d’obtenir des réponses sécurisées et conformes à la gouvernance. Vous apprendrez ce qu’est un Genie Space, comment il protège vos données et les meilleures pratiques pour obtenir des résultats optimaux. Le cours se termine par un jeu pratique où vous serez en compétition pour enquêter sur un mystère commercial.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30342","entityUrl":{"path":"/fr/training/catalog/agent-evaluation-on-databricks-french-5996"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/agent-evaluation-on-databricks-french-5996"}}],"nid":30342,"vid":236791,"title":"Agent Evaluation on Databricks - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours apprend aux étudiants à évaluer systématiquement les agents IA à l’aide du cadre d’évaluation de MLflow, en répondant aux défis propres aux systèmes d’IA non déterministes que les tests logiciels traditionnels ne peuvent pas gérer. Les étudiants apprennent à mettre en œuvre différentes approches d’évaluation, notamment des juges intégrés pour des critères courants tels que l’exactitude et la sécurité, des juges de directives pour des exigences propres à l’entreprise, et des juges personnalisés pour des besoins spécialisés. Le cours couvre à la fois l’évaluation hors ligne à partir d’ensembles de données organisés et le monitoring en ligne en production, avec une expérience pratique des capacités de traçage de MLflow pour comprendre les schémas d’exécution des agents et recueillir les retours humains de différents types de parties prenantes. À travers des démonstrations pratiques et des laboratoires, les étudiants développent des compétences pour créer des workflows d’évaluation qui favorisent l’amélioration continue de la qualité tout au long du cycle de vie de développement des agents IA.
Remarque : Databricks Academy passe à un format basé sur des notebooks pour les sessions en classe dans l’environnement Databricks, et n’utilise plus de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l’environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30316","entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-5985"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-agentic-applications-on-databricks-french-5985"}}],"nid":30316,"vid":236687,"title":"Building Agentic Applications on Databricks - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours enseigne aux étudiants comment créer des applications agentiques de niveau production sur Databricks. Les étudiants apprennent à créer des outils d’agent gouvernés avec Unity Catalog et MCP, à construire des systèmes mono-agent et multi-agents avec le OpenAI Agents SDK, et à tirer parti d’Agent Bricks et de Genie pour des cas d’usage de knowledge assistant orchestrés par un agent supervisor. Le cours couvre l’ensemble du parcours, du prototypage d’outils au déploiement en production, avec une pratique du tracing MLflow pour observer l’exécution des agents.
Remarque : La Databricks Academy est en train de passer à un format basé sur des notebooks pour les sessions en classe au sein de l'environnement Databricks, en abandonnant l'utilisation de présentations de diapositives pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30303","entityUrl":{"path":"/fr/training/catalog/building-rag-agents-with-agent-bricks-french-5961"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-rag-agents-with-agent-bricks-french-5961"}}],"nid":30303,"vid":236660,"title":"Building RAG Agents with Agent Bricks - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours propose une formation pratique pour créer des agents de récupération avec Databricks Agent Bricks. Les participants apprendront à explorer et interroger des Knowledge Assistants, à transformer des documents non structurés en données structurées avec les AI Functions, à découper le texte pour la récupération sémantique, à créer des index AI Search, et à concevoir des Knowledge Assistants prêts pour la production s’appuyant sur plusieurs sources de connaissances.
Remarque : La Databricks Academy est en train de passer à un format basé sur des notebooks pour les sessions en classe au sein de l'environnement Databricks, en abandonnant l'utilisation de présentations de diapositives pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30305","entityUrl":{"path":"/fr/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-french-5977"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-french-5977"}}],"nid":30305,"vid":236662,"title":"Deploying and Monitoring Agent Applications on Databricks - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours couvre le cycle de vie de bout en bout pour le déploiement et la surveillance d’agents d’IA générative sur Databricks. Les participants apprendront à déployer des agents en tant que Databricks Apps à l’aide de Declarative Automation Bundles (DABs), à intégrer des outils via le Model Context Protocol (MCP), à instrumenter les agents avec MLflow Tracing, et à évaluer la qualité en production à l’aide de scorers, de juges multi-tours et d’une évaluation en ligne. Grâce à des démos et labs pratiques, les participants acquerront une expérience concrète de création, d’observation et de surveillance d’agents IA de niveau production sur la plateforme Databricks.
Remarque : Databricks Academy passe à un format basé sur des notebooks pour les sessions en classe dans l’environnement Databricks, et n’utilise plus de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l’environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"29850","entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4244"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4244"}}],"nid":29850,"vid":235502,"title":"AI/BI for Data Analysts - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours apprend aux analystes de données à concevoir, créer, publier et exploiter des AI/BI Dashboards dans Databricks. Les AI/BI Dashboards associent des données gouvernées par Unity Catalog à des visualisations interactives, des filtres et l'intégration de Genie, afin que les utilisateurs métier puissent explorer les réponses sans écrire de code.
Le cours suit une seule réalisation de bout en bout. Vous commencez avec des tables sources dans Unity Catalog et terminez avec un tableau de bord multipage publié et surveillé. En chemin, vous découvrez comment les tableaux de bord s'intègrent dans la famille de produits AI/BI de Databricks et où interviennent Genie, les jeux de données, les visualisations et les filtres dans le flux de travail.
Le contenu couvre :
• Les principes fondamentaux des AI/BI Dashboards et leur relation avec Genie et le reste de la plateforme Databricks.
• L'exploration des données sources dans Unity Catalog et la conception de jeux de données de tableau de bord réutilisables avec SQL.
• La création de visualisations (KPI, tendances, répartitions) et la mise en page d'un tableau de bord multipage soigné.
• L'utilisation de Genie Code pour générer du SQL, des graphiques et des filtres à partir de prompts en langage naturel.
• L'ajout de filtres pour rendre les tableaux de bord interactifs et réactifs aux questions des utilisateurs.
• La publication, le partage et la gestion des autorisations afin que les bonnes personnes puissent consulter et modifier le tableau de bord.
• L'exploitation du tableau de bord en production avec actualisation planifiée, mise en cache et suivi de l'utilisation.
À la fin du cours, vous serez en mesure de partir d'une question métier, de concevoir les jeux de données nécessaires, de créer un tableau de bord abouti et de le livrer à votre audience avec les autorisations appropriées et une stratégie d'actualisation qui en garantit l'exactitude.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29851","entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4245"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4245"}}],"nid":29851,"vid":235503,"title":"AI/BI for Data Analysts - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours apprend aux analystes de données à concevoir, créer, publier et exploiter des AI/BI Dashboards dans Databricks. Les AI/BI Dashboards associent des données gouvernées par Unity Catalog à des visualisations interactives, des filtres et l'intégration de Genie, afin que les utilisateurs métier puissent explorer les réponses sans écrire de code.
Le cours suit une seule réalisation de bout en bout. Vous commencez avec des tables sources dans Unity Catalog et terminez avec un tableau de bord multipage publié et surveillé. En chemin, vous découvrez comment les tableaux de bord s'intègrent dans la famille de produits AI/BI de Databricks et où interviennent Genie, les jeux de données, les visualisations et les filtres dans le flux de travail.
Le contenu couvre :
• Les principes fondamentaux des AI/BI Dashboards et leur relation avec Genie et le reste de la plateforme Databricks.
• L'exploration des données sources dans Unity Catalog et la conception de jeux de données de tableau de bord réutilisables avec SQL.
• La création de visualisations (KPI, tendances, répartitions) et la mise en page d'un tableau de bord multipage soigné.
• L'utilisation de Genie Code pour générer du SQL, des graphiques et des filtres à partir de prompts en langage naturel.
• L'ajout de filtres pour rendre les tableaux de bord interactifs et réactifs aux questions des utilisateurs.
• La publication, le partage et la gestion des autorisations afin que les bonnes personnes puissent consulter et modifier le tableau de bord.
• L'exploitation du tableau de bord en production avec actualisation planifiée, mise en cache et suivi de l'utilisation.
À la fin du cours, vous serez en mesure de partir d'une question métier, de concevoir les jeux de données nécessaires, de créer un tableau de bord abouti et de le livrer à votre audience avec les autorisations appropriées et une stratégie d'actualisation qui en garantit l'exactitude.
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
Dans ce cours, vous apprendrez à concevoir, implémenter et gouverner les structures de catalog et l'organisation de données à grande échelle sur la Databricks Data Intelligence Platform. Il offre une vue complète d'Unity Catalog comme couche de gouvernance centralisée pour un lakehouse d'entreprise. Divisé en cinq modules, il commence par placer Unity Catalog dans le modèle de déploiement cloud — couvrant la Account Console, création de metastore et hiérarchie de rôles d'administrateur. Vous traduirez ensuite la topologie organisationnelle (unités commerciales, régions et environnements dev/QA/prod) en une conception évolutive de catalog et schema utilisant les conventions de nommage, patterns de propriété et délégation MANAGE. Le cours couvre ensuite l'intégration de stockage sécurisée avec credentials de stockage, emplacements externes, hiérarchie managed-storage, tables gérées versus externes et UC Volumes pour les données non-tabulaires. Ensuite, vous appliquerez les patterns d'accès et stratégies d'isolation — la chaîne GRANT à trois niveaux, liaison workspace-catalog et politiques Attribute-Based Access Control (ABAC) au niveau schema — pour faire respecter la protection de données à grain fin à grande échelle. Enfin, le cours se termine par les meilleures pratiques pour la conception de catalog, automation, permissions de moindre privilège et gestion d'accès basée sur les groupes.
Remarque : La Databricks Academy est en train de passer à un format basé sur des notebooks pour les sessions en classe au sein de l'environnement Databricks, en abandonnant l'utilisation de présentations de diapositives pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29793","entityUrl":{"path":"/fr/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-french-5906"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-french-5906"}}],"nid":29793,"vid":234753,"title":"Business Impact Accelerator: Answering Business Questions with Genie - French","price":"0.00","duration":10800,"body":{"processed":"Ce cours présente Databricks Génie One, un environnement de travail collaboratif alimenté par l'IA, conçu autour de vos besoins et de votre travail, où vous pouvez poser des questions en langage naturel sur les données de votre organisation et obtenir des réponses sécurisées et gouvernées, établir le planning des rapports à exécuter automatiquement, et automatiser votre workflow pour accomplir davantage de travail plus rapidement et avec plus de précision, car il repose sur vos données et votre activité. Vous apprendrez ce que sont Génie, Génie One et les agents Génie, comment ils assurent la sécurité de vos données, ainsi que les meilleures pratiques pour obtenir les meilleurs résultats.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29759","entityUrl":{"path":"/fr/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-french-3952"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-french-3952"}}],"nid":29759,"vid":234461,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI) - French","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
Ce cours présente les compétences fondamentales nécessaires pour réaliser un workflow de base d’ingénierie des données sur la Databricks Data Intelligence Platform. Vous explorerez l’espace de travail, travaillerez avec Unity Catalog et découvrirez les éléments de base qu’un ingénieur de données utilise au quotidien sur Databricks.
Le cours suit une approche pratique. Vous commencez par vous familiariser avec l’espace de travail, puis vous progressez à travers des notebooks de démo et d’atelier associés pour chaque sujet. Les démos vous présentent un concept avec le formateur ou un notebook guidé ; les ateliers vous demandent d’appliquer par vous-même ce que vous venez de voir.
Get Started with SQL Analytics and BI on Databricks
Dans ce cours, vous apprendrez les compétences de base qui vous permettront d'utiliser la Plateforme de Data Intelligence Databricks pour effectuer un flux de travail d'analyse de données simple et soutenir les efforts d'entreposage de données.Vous bénéficierez d'une visite de l'espace de travail et découvrirez comment travailler avec des objets de données dans Databricks tels que des catalogues, des schémas, des tables, des clusters de calcul, des blocs-notes et des tableaux de bord.Vous suivrez ensuite un flux de travail d'analyse de données de base pour effectuer des tâches telles que la manipulation de données à l'aide de Databricks SQL, l'exploitation des logs de version Delta Lake pour voyager dans le temps, la création de tableaux de bord au sein de la plateforme et la création d'espaces Genie pour l'exploration de données à l'aide d'invites en langage naturel.Vous apprendrez également comment Databricks prend en charge les besoins d’entreposage de données grâce à l’utilisation de Databricks SQL, Delta Live Tables et Unity Catalog.Avec l'achat d'un abonnement Databricks Labs, le cours se termine également par un exercice de laboratoire
Vous pouvez créer un Databricks Free Edition account et essayer les démonstrations pas à pas dans un environnement pratique.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-09-30T09:00:00"},"endDate":{"value":"2026-09-30T13:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-12-11T09:00:00"},"endDate":{"value":"2026-12-11T13:00:00"},"timezone":"Europe/Paris"}}]},{"id":"29750","entityUrl":{"path":"/fr/training/catalog/machine-learning-model-development-french-5885"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/machine-learning-model-development-french-5885"}}],"nid":29750,"vid":234427,"title":"Machine Learning Model Development - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours complet offre un guide pratique pour développer des modèles de machine learning traditionnels sur Databricks, en mettant l'accent sur des démonstrations pratiques et des workflows utilisant les bibliothèques de ML les plus courantes. Les participants exploreront des techniques de ML essentielles, notamment la régression et le clustering, tout en tirant parti des puissantes capacités de Databricks. Le cours couvre l'intégration de MLflow pour le suivi des modèles, le Databricks Feature Store pour la gestion des features, et Optuna pour l'optimisation des hyperparamètres. Les participants apprendront en outre à accélérer le développement de modèles avec Genie Code, l'assistant de codage IA de Databricks qui utilise le langage naturel, des connexions MCP, des instructions et des compétences pour guider l'ensemble du cycle de vie du ML. À la fin du cours, les apprenants disposeront de compétences pratiques et concrètes pour développer, optimiser et déployer efficacement des modèles de machine learning dans l'environnement Databricks.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"29635","entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5881"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5881"}}],"nid":29635,"vid":234141,"title":"Get Started with Lakebase - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours de démarrage présente Databricks Lakebase, un service PostgreSQL Entièrement géré intégré à la Databricks Data Intelligence Platform, qui rapproche les charges de travail opérationnelles (OLTP) et analytiques (OLAP).
Le cours débute par un exposé conceptuel comparant les systèmes OLTP et OLAP, en expliquant leurs caractéristiques de performance respectives, leurs modèles de stockage et leurs cas d'usage typiques. Vous explorerez également les défis auxquels font face les organisations qui maintiennent des bases de données transactionnelles et des plateformes d'analyse de données séparées, notamment en matière de déplacement des données, de latence et de complexité architecturale.
Vous découvrirez ensuite comment Databricks Lakebase contribue à relever ces défis en fournissant une base de données opérationnelle compatible PostgreSQL qui s'intègre directement au Databricks Lakehouse, permettant ainsi aux applications opérationnelles et à l'analyse de données de fonctionner ensemble au sein d'une plateforme unifiée.
À travers des travaux pratiques, vous allez:
Créer et Explorer un projet Lakebase en utilisant un compute à mise à l'échelle automatique
• Naviguer dans l'interface utilisateur de Lakebase, notamment les fonctionnalités de branchement, de monitoring et les paramètres de configuration
• Créer des tables et les interroger à l'aide de l'éditeur SQL de Lakebase
• Interroger les données Lakebase depuis Databricks en utilisant Lakehouse Federation et des catalogues étrangers
• Effectuer un Reverse ETL en synchronisant des tables Delta vers Lakebase
• Se connecter à Lakebase depuis Python et effectuer des opérations CRUD de base
Il s'agit d'un cours de démarrage ; l'accent est donc mis sur la compréhension des concepts fondamentaux et des flux de travail de base pour travailler avec Lakebase. La création d'applications de production complètes sur Lakebase dépasse le cadre de ce cours.
À l'issue du cours, vous comprendrez comment Lakebase permet aux organisations de rapprocher les systèmes opérationnels et l'analyse de données au sein d'une plateforme unique et gouvernée, propulsée par Unity Catalog et le Databricks Lakehouse.
Remarque : pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM après avoir terminé le contenu. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29616","entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-5827"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/sql-programming-and-procedural-logic-french-5827"}}],"nid":29616,"vid":234122,"title":"SQL Programming and Procedural Logic - French","price":"750.00","duration":14400,"body":{"processed":"Dans ce cours, vous explorerez les compétences essentielles en programmation SQL et logique procédurale dans Databricks, en vous concentrant sur la création de flux de travail analytiques modulaires, maintenables et prêts pour la production. Vous commencerez par découvrir les constructions SQL clés — telles que les Common Table Expressions (y compris les CTE récursives avancées), les objets à portée de session comme les vues et tables temporaires, et les User Defined Functions — qui rendent votre développement SQL plus propre et réutilisable. Le cours vous guide ensuite à travers des techniques avancées de scripting SQL à l'aide d'instructions composées, de variables, de flux de contrôle, de conditions, de boucles et d'une gestion robuste des erreurs pour créer des processus SQL structurés et flexibles. Vous apprendrez également à garantir la cohérence des données dans ces pipelines en plusieurs étapes grâce à des transactions multi-instructions conformes ACID. Enfin, vous découvrirez comment encapsuler la logique dans des SQL Stored Procedures et orchestrer des flux de travail complexes avec Lakeflow Jobs et des stratégies de migration, transformant les tâches héritées en pipelines modulaires et automatisés qui exploitent toutes les capacités de la plateforme Databricks.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29442","entityUrl":{"path":"/fr/training/catalog/building-reliable-conversational-agents-with-genie-french-5790"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-reliable-conversational-agents-with-genie-french-5790"}}],"nid":29442,"vid":232863,"title":"Building Reliable Conversational Agents with Genie - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours vous apprend à concevoir, créer et gérer un espace Databricks Genie (Genie Space), une interface en langage naturel permettant aux utilisateurs métier de poser des questions sur des données gouvernées et d'obtenir des réponses basées sur SQL, sans avoir à écrire de code.
Vous découvrirez la place de Genie au sein de la gamme de produits Databricks AI/BI et la manière dont l'outil traduit le langage naturel en requêtes SQL fiables. La formation met l'accent sur les étapes nécessaires à la création d'un espace Genie fournissant des résultats précis, cohérents et dignes de confiance.
Vous suivrez un flux de travail complet, de la compréhension des données sources et de la définition de points de référence jusqu'à la configuration et l'affinage d'un espace Genie, en utilisant l'ensemble des outils de curation du « Knowledge Store ». Ces outils incluent la gestion des métadonnées, des synonymes, de la correspondance des prompts, de la logique SQL, des exemples de requêtes et des instructions textuelles.
Vous apprendrez également à partager les espaces Genie avec les utilisateurs métier via Databricks One, à comprendre comment la gouvernance d'Unity Catalog est appliquée automatiquement, et à utiliser la surveillance ainsi que les retours des utilisateurs pour améliorer continuellement la qualité au fil du temps.
À l'issue de ce cours, vous serez capable de créer et de gérer un espace Genie prêt pour la production, offrant des analyses conversationnelles en libre-service et gouvernées, à grande échelle.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29429","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-5769"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-5769"}}],"nid":29429,"vid":232663,"title":"Get Started with Databricks for Data Engineering - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente les compétences fondamentales nécessaires pour réaliser un workflow de base d’ingénierie des données sur la Databricks Data Intelligence Platform. Vous explorerez l’espace de travail, travaillerez avec Unity Catalog et découvrirez les éléments de base qu’un ingénieur de données utilise au quotidien sur Databricks.
Le cours suit une approche pratique. Vous commencez par vous familiariser avec l’espace de travail, puis vous progressez à travers des notebooks de démo et d’atelier associés pour chaque sujet. Les démos vous présentent un concept avec le formateur ou un notebook guidé ; les ateliers vous demandent d’appliquer par vous-même ce que vous venez de voir.
Le contenu couvre les points suivants :
• La Databricks Data Intelligence Platform et la façon dont l’espace de travail Databricks, Unity Catalog et les notebooks s’articulent.
• La création et la gestion de tables Delta Lake.
• La modification des données avec INSERT, UPDATE et DELETE.
• L’exploration de l’historique des versions et du time travel sur les tables Delta.
• L’ingestion de données avec les options de Lakeflow Connect : CTAS, l’interface d’importation (Upload UI) et COPY INTO.
• La création d’un pipeline d’architecture Medallion qui transforme les données à travers les couches Bronze, Silver et Gold.
• L’automatisation des pipelines avec Lakeflow Jobs.
• (Bonus) La création d’un pipeline déclaratif avec Spark Declarative Pipelines.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29430","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-5770"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-5770"}}],"nid":29430,"vid":232664,"title":"Get Started with Databricks for Data Engineering - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours présente les compétences fondamentales nécessaires pour réaliser un workflow de base d’ingénierie des données sur la Databricks Data Intelligence Platform. Vous explorerez l’espace de travail, travaillerez avec Unity Catalog et découvrirez les éléments de base qu’un ingénieur de données utilise au quotidien sur Databricks.
Le cours suit une approche pratique. Vous commencez par vous familiariser avec l’espace de travail, puis vous progressez à travers des notebooks de démo et d’atelier associés pour chaque sujet. Les démos vous présentent un concept avec le formateur ou un notebook guidé ; les ateliers vous demandent d’appliquer par vous-même ce que vous venez de voir.
Le contenu couvre les points suivants :
• La Databricks Data Intelligence Platform et la façon dont l’espace de travail Databricks, Unity Catalog et les notebooks s’articulent.
• La création et la gestion de tables Delta Lake.
• La modification des données avec INSERT, UPDATE et DELETE.
• L’exploration de l’historique des versions et du time travel sur les tables Delta.
• L’ingestion de données avec les options de Lakeflow Connect : CTAS, l’interface d’importation (Upload UI) et COPY INTO.
• La création d’un pipeline d’architecture Medallion qui transforme les données à travers les couches Bronze, Silver et Gold.
• L’automatisation des pipelines avec Lakeflow Jobs.
• (Bonus) La création d’un pipeline déclaratif avec Spark Declarative Pipelines.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29376","entityUrl":{"path":"/fr/training/catalog/lakebase-app-integration-and-management-french-5689"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/lakebase-app-integration-and-management-french-5689"}}],"nid":29376,"vid":231404,"title":"Lakebase App Integration and Management - French","price":"750.00","duration":14400,"body":{"processed":"Dans ce cours, vous apprendrez à intégrer Databricks Apps à Lakebase, la plateforme PostgreSQL entièrement gérée et cloud-native de Databricks, afin de créer des workflows d'application sécurisés et prêts pour l'entreprise. En s'appuyant sur les connaissances fondamentales de Databricks Apps et de Lakebase, ce cours met l'accent sur les fondamentaux de PostgreSQL, Lakebase Autoscaling, les pratiques SQL sécurisées, la gestion sécurisée des connexions, l'accès basé sur les rôles, l'intégration de la Data API et le développement basé sur les branches. Vous découvrirez également comment AppKit peut accélérer le développement d'applications au sein de ce workflow, en vous aidant à passer plus efficacement des concepts d'intégration à leur mise en œuvre.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29372","entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5674"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-lakebase-french-5674"}}],"nid":29372,"vid":231262,"title":"Get Started with Lakebase - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours de démarrage présente Databricks Lakebase, un service PostgreSQL Entièrement géré intégré à la Databricks Data Intelligence Platform, qui rapproche les charges de travail opérationnelles (OLTP) et analytiques (OLAP).
Le cours débute par un exposé conceptuel comparant les systèmes OLTP et OLAP, en expliquant leurs caractéristiques de performance respectives, leurs modèles de stockage et leurs cas d'usage typiques. Vous explorerez également les défis auxquels font face les organisations qui maintiennent des bases de données transactionnelles et des plateformes d'analyse de données séparées, notamment en matière de déplacement des données, de latence et de complexité architecturale.
Vous découvrirez ensuite comment Databricks Lakebase contribue à relever ces défis en fournissant une base de données opérationnelle compatible PostgreSQL qui s'intègre directement au Databricks Lakehouse, permettant ainsi aux applications opérationnelles et à l'analyse de données de fonctionner ensemble au sein d'une plateforme unifiée.
Il s'agit d'un cours de démarrage ; l'accent est donc mis sur la compréhension des concepts fondamentaux et des flux de travail de base pour travailler avec Lakebase. La création d'applications de production complètes sur Lakebase dépasse le cadre de ce cours.
À l'issue du cours, vous comprendrez comment Lakebase permet aux organisations de rapprocher les systèmes opérationnels et l'analyse de données au sein d'une plateforme unique et gouvernée, propulsée par Unity Catalog et le Databricks Lakehouse.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29368","entityUrl":{"path":"/fr/training/catalog/building-enterprise-applications-with-databricks-apps-french-5631"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-enterprise-applications-with-databricks-apps-french-5631"}}],"nid":29368,"vid":231104,"title":"Building Enterprise Applications with Databricks Apps - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours présente Databricks Apps, une nouvelle fonctionnalité qui permet aux développeurs de créer et de déployer des applications de données et d'IA sécurisées directement sur la plateforme Databricks. Il s'adresse principalement aux data scientists, aux ingénieurs de données et aux développeurs qui doivent créer des applications personnalisées rendant les insights de données accessibles aux utilisateurs non techniques de leur organisation.
Le cours commence par une présentation des principaux composants de Databricks Apps, suivie du déploiement d'une application simple intégrée à un service externe. Vous apprendrez ensuite à créer et à déployer des applications intelligentes et pilotées par les données, intégrées aux fonctionnalités de la plateforme Databricks. Le cours explique également comment développer des applications en dehors de l'environnement Databricks. Il se conclut par un traitement détaillé des bonnes pratiques pour mettre en œuvre des applications d'entreprise sécurisées et fiables.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | 한국어 | Español | Português BR
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29295","entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5607"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5607"}}],"nid":29295,"vid":229973,"title":"Building ETL Pipelines with SQL - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours enseigne comment créer des pipelines ETL prêts pour la production en utilisant exclusivement SQL sur la Databricks Data Intelligence Platform. Les participants découvrent les Streaming Tables avec Auto Loader pour l'ingestion incrémentielle, les Materialized Views avec rafraîchissement incrémentiel pour les transformations Silver vers Gold, AUTO CDC (FLOW AUTO CDC) pour la gestion déclarative des dimensions SCD Type 1 et Type 2, ainsi que Lakeflow Jobs avec des tâches SQL File pour l'orchestration en production. Le cours suit un jeu de données retail réaliste à travers l'architecture en médaillon (Bronze → Silver → Gold).
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29296","entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5611"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5611"}}],"nid":29296,"vid":229974,"title":"Building ETL Pipelines with SQL - French","price":"75.00","duration":10800,"body":{"processed":"Ce cours enseigne comment créer des pipelines ETL prêts pour la production en utilisant exclusivement SQL sur la Databricks Data Intelligence Platform. Les participants découvrent les Streaming Tables avec Auto Loader pour l'ingestion incrémentielle, les Materialized Views avec rafraîchissement incrémentiel pour les transformations Silver vers Gold, AUTO CDC (FLOW AUTO CDC) pour la gestion déclarative des dimensions SCD Type 1 et Type 2, ainsi que Lakeflow Jobs avec des tâches SQL File pour l'orchestration en production. Le cours suit un jeu de données retail réaliste à travers l'architecture en médaillon (Bronze → Silver → Gold).
Remarque: pour les fichiers de cours SCORM, veillez à fermer la fenêtre SCORM une fois le contenu terminé. Ne cliquez pas sur le bouton « Next Lesson », car cela pourrait empêcher le module SCORM d'être marqué comme terminé.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29223","entityUrl":{"path":"/fr/training/catalog/architecting-data-warehouses-for-large-scale-deployments-french-5499"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/architecting-data-warehouses-for-large-scale-deployments-french-5499"}}],"nid":29223,"vid":229405,"title":"Architecting Data Warehouses for Large-Scale Deployments - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours traite de l'optimisation des performances, de la maîtrise des coûts et de la sécurité pour les déploiements de data warehousing à grande échelle.
Ce cours s'adresse aux praticiens du data warehousing chargés de gérer des environnements Databricks au service de centaines ou de milliers d'utilisateurs répartis dans plusieurs unités opérationnelles. Vous acquerrez les compétences nécessaires pour faire évoluer efficacement les opérations de data warehousing tout en maintenant des performances élevées, une bonne rentabilité et la conformité aux normes de sécurité.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29078","entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5536"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/building-etl-pipelines-with-sql-french-5536"}}],"nid":29078,"vid":228199,"title":"Building ETL Pipelines with SQL - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours enseigne comment créer des pipelines ETL prêts pour la production en utilisant du SQL pur sur la Databricks Data Intelligence Platform. Les étudiants apprennent les Streaming Tables avec Auto Loader pour l'ingestion incrémentielle, les Vues Matérialisées avec rafraîchissement incrémentiel pour les transformations Bronze vers Argent, l'AUTO CDC (FLOW AUTO CDC) pour la gestion déclarative des dimensions SCD de Type 1 et Type 2, ainsi qu'Apache Spark Declarative Pipelines (SDP) pour regrouper ces objets en pipelines multi-tables de production avec des attentes de qualité des données, des tables PRIVATE et un monitoring unifié. Le cours suit un ensemble de données de vente au détail réaliste à travers la Medallion Architecture (Bronze → Argent → Gold). L'orchestration avec Lakeflow Jobs est disponible en tant que module bonus.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28512","entityUrl":{"path":"/fr/training/catalog/data-analysis-with-databricks-french-5313"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-analysis-with-databricks-french-5313"}}],"nid":28512,"vid":218100,"title":"Data Analysis with Databricks - French","price":"1000.00","duration":28800,"body":{"processed":"SQL Analytics on Databricks
Dans ce cours, vous apprendrez à utiliser efficacement Databricks pour l’analyse de données, en mettant l’accent sur Databricks SQL. En tant qu’analyste de données Databricks, vos responsabilités comprendront la recherche de données pertinentes, l’analyse des données pour des applications potentielles et la transformation des données en formats qui fournissent des insights commerciaux précieux.
Vous comprendrez également votre rôle dans la gestion des objets de données et comment les manipuler au sein du Databricks Data Intelligence Platform, à l’aide d’outils tels que Notebooks, l’éditeur SQL et Databricks SQL.
De plus, vous découvrirez l’importance de Unity Catalog dans la gestion des actifs de données et de la plateforme globale. Enfin, le cours fournira un aperçu de la façon dont Databricks facilite l’optimisation des performances et vous apprendra comment accéder à Query Insights pour comprendre les processus qui se déroulent en coulisse lors de l’exécution de l’analyse SQL sur Databricks.
AI/BI for Data Analysts
Ce cours apprend aux analystes de données à concevoir, créer, publier et exploiter des AI/BI Dashboards dans Databricks. Les AI/BI Dashboards associent des données gouvernées par Unity Catalog à des visualisations interactives, des filtres et l'intégration de Genie, afin que les utilisateurs métier puissent explorer les réponses sans écrire de code.
Le cours suit une seule réalisation de bout en bout. Vous commencez avec des tables sources dans Unity Catalog et terminez avec un tableau de bord multipage publié et surveillé. En chemin, vous découvrez comment les tableaux de bord s'intègrent dans la famille de produits AI/BI de Databricks et où interviennent Genie, les jeux de données, les visualisations et les filtres dans le flux de travail.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
\n\n \nLanguages Available: English | 日本語 | Português BR | 한국어\n
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28222","entityUrl":{"path":"/fr/training/catalog/sql-analytics-on-databricks-french-4951"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/sql-analytics-on-databricks-french-4951"}}],"nid":28222,"vid":217527,"title":"SQL Analytics on Databricks - French","price":"750.00","duration":14400,"body":{"processed":"Dans ce cours, vous apprendrez à utiliser efficacement Databricks pour l’analyse de données, en mettant l’accent sur Databricks SQL. En tant qu’analyste de données Databricks, vos responsabilités comprendront la recherche de données pertinentes, l’analyse des données pour des applications potentielles et la transformation des données en formats qui fournissent des insights commerciaux précieux.
Vous comprendrez également votre rôle dans la gestion des objets de données et comment les manipuler au sein du Databricks Data Intelligence Platform, à l’aide d’outils tels que Notebooks, l’éditeur SQL et Databricks SQL.
De plus, vous découvrirez l’importance de Unity Catalog dans la gestion des actifs de données et de la plateforme globale. Enfin, le cours fournira un aperçu de la façon dont Databricks facilite l’optimisation des performances et vous apprendra comment accéder à Query Insights pour comprendre les processus qui se déroulent en coulisse lors de l’exécution de l’analyse SQL sur Databricks.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28416","entityUrl":{"path":"/fr/training/catalog/databricks-fundamentals-accreditation-french-3716"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/databricks-fundamentals-accreditation-french-3716"}}],"nid":28416,"vid":217721,"title":"Databricks Fundamentals Accreditation - French","price":"0.00","duration":1800,"body":{"processed":"Bienvenue dans l’Accréditation Databricks Fundamentals. Dans ce questionnaire de 10 questions, nous évaluerons vos connaissances de la Databricks Data Intelligence Platform. Une fois ce questionnaire réussi, un badge vous sera attribué (dans un délai de 48 heures) par notre fournisseur de badges, Accredible. Bonne chance !
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"28422","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-3751"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-generative-ai-french-3751"}}],"nid":28422,"vid":217727,"title":"Get Started with Databricks for Generative AI - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours offre une introduction pratique à la Databricks Data Intelligence Platform, en mettant l'accent sur ses composants et fonctionnalités clés pour la création et le déploiement de systèmes d'IA générative. Les participants apprendront comment Databricks facilite le développement de solutions d'IA générative évolutives et exploreront des outils tels que AI Search, le Cadre Agent et les capacités d'IA générative de MLflow pour le suivi et l'enregistrement des modèles. Ce cours comprend une expérience pratique dans la construction et l'évaluation de pipelines Retrieval-Augmented Generation (RAG), le déploiement d'agents d'IA générative, et l'utilisation de cadres d'évaluation pour optimiser la performance. À la fin du cours, les apprenants seront équipés des compétences nécessaires pour concevoir, déployer et surveiller des applications courantes d'IA générative sur la Databricks Data Intelligence Platform.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-23T14:00:00"},"endDate":{"value":"2026-10-23T16:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2027-01-21T14:00:00"},"endDate":{"value":"2027-01-21T16:00:00"},"timezone":"Europe/Paris"}}]},{"id":"28423","entityUrl":{"path":"/fr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-french-3760"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-french-3760"}}],"nid":28423,"vid":217728,"title":"Get Started with SQL Analytics and BI on Databricks - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente la Databricks Data Intelligence Platform et les compétences fondamentales dont un analyste de données a besoin pour ses activités quotidiennes d'analyse de données SQL et de BI. Vous apprendrez à naviguer dans le workspace et Unity Catalog, à écrire des requêtes SQL sur des tables gérées par Unity Catalog depuis un Serverless SQL Warehouse, à utiliser Genie Code pour générer et déboguer du SQL, à travailler avec Delta Lake (DML, historique des versions, time travel et restauration), à créer et publier des Tableaux de bord IA/BI, et à créer des Génie Agents pour l'analyse de données conversationnelle.
Vous pouvez créer un compte Databricks Free Edition et essayer les démonstrations à suivre dans un environnement pratique.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2409,"name":"Docebo"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28053","entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-3933"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/get-started-with-databricks-for-data-engineering-french-3933"}}],"nid":28053,"vid":217358,"title":"Get Started with Databricks for Data Engineering - French","price":"0.00","duration":7200,"body":{"processed":"Ce cours présente les compétences fondamentales nécessaires pour réaliser un workflow de base d’ingénierie des données sur la Databricks Data Intelligence Platform. Vous explorerez l’espace de travail, travaillerez avec Unity Catalog et découvrirez les éléments de base qu’un ingénieur de données utilise au quotidien sur Databricks.
Le cours suit une approche pratique. Vous commencez par vous familiariser avec l’espace de travail, puis vous progressez à travers des notebooks de démo et d’atelier associés pour chaque sujet. Les démos vous présentent un concept avec le formateur ou un notebook guidé ; les ateliers vous demandent d’appliquer par vous-même ce que vous venez de voir.
Le contenu couvre les points suivants:
• La Databricks Data Intelligence Platform et la façon dont l’espace de travail Databricks, Unity Catalog et les notebooks s’articulent.
• La création et la gestion de tables Delta Lake.
• La modification des données avec INSERT, UPDATE et DELETE.
• L’exploration de l’historique des versions et du time travel sur les tables Delta.
• L’ingestion de données avec les options de Lakeflow Connect : CTAS, l’interface d’importation (Upload UI) et COPY INTO.
• La création d’un pipeline d’architecture Medallion qui transforme les données à travers les couches Bronze, Silver et Gold.
• L’automatisation des pipelines avec Lakeflow Jobs.
• (Bonus) La création d’un pipeline déclaratif avec Spark Declarative Pipelines.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-28T14:00:00"},"endDate":{"value":"2026-10-28T16:00:00"},"timezone":"Europe/Paris"}}]},{"id":"28086","entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4047"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/aibi-for-data-analysts-french-4047"}}],"nid":28086,"vid":217391,"title":"AI/BI for Data Analysts - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours apprend aux analystes de données à concevoir, créer, publier et exploiter des AI/BI Dashboards dans Databricks. Les AI/BI Dashboards associent des données gouvernées par Unity Catalog à des visualisations interactives, des filtres et l'intégration de Genie, afin que les utilisateurs métier puissent explorer les réponses sans écrire de code.
Le cours suit une seule réalisation de bout en bout. Vous commencez avec des tables sources dans Unity Catalog et terminez avec un tableau de bord multipage publié et surveillé. En chemin, vous découvrez comment les tableaux de bord s'intègrent dans la famille de produits AI/BI de Databricks et où interviennent Genie, les jeux de données, les visualisations et les filtres dans le flux de travail.
Le contenu couvre :
• Les principes fondamentaux des AI/BI Dashboards et leur relation avec Genie et le reste de la plateforme Databricks.
• L'exploration des données sources dans Unity Catalog et la conception de jeux de données de tableau de bord réutilisables avec SQL.
• La création de visualisations (KPI, tendances, répartitions) et la mise en page d'un tableau de bord multipage soigné.
• L'utilisation de Genie Code pour générer du SQL, des graphiques et des filtres à partir de prompts en langage naturel.
• L'ajout de filtres pour rendre les tableaux de bord interactifs et réactifs aux questions des utilisateurs.
• La publication, le partage et la gestion des autorisations afin que les bonnes personnes puissent consulter et modifier le tableau de bord.
• L'exploitation du tableau de bord en production avec actualisation planifiée, mise en cache et suivi de l'utilisation.
Remarque: Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28135","entityUrl":{"path":"/fr/training/catalog/generative-ai-fundamentals-accreditation-french-4284"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/generative-ai-fundamentals-accreditation-french-4284"}}],"nid":28135,"vid":217440,"title":"Generative AI Fundamentals Accreditation - French","price":"0.00","duration":900,"body":{"processed":"Il s’agit d’une évaluation de 20 minutes qui testera vos connaissances des concepts fondamentaux liés à l'IA générative.
Après avoir réussi cette évaluation, vous recevrez le badge Databricks Generative AI Fundamentals.
Parcours d’apprentissage
• Cette accréditation fait partie du plan d’apprentissage Databricks Generative AI Fundamentals.
Preuve d’achèvement
• À partir d’un taux de réussite de 80 %, vous recevrez un badge de Databricks.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"28144","entityUrl":{"path":"/fr/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-french-4444"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-french-4444"}}],"nid":28144,"vid":217449,"title":"Build Data Pipelines with Apache Spark™ Declarative Pipelines - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours présente aux utilisateurs les concepts essentiels et les compétences nécessaires pour construire des pipelines de données à l'aide d'Apache Spark™ Pipeline déclaratifs (SDP) dans Databricks pour l'ingestion et le traitement incrémentaux en mode batch ou streaming à travers plusieurs tables streaming et vues matérialisées. Conçu pour les ingénieurs de données qui découvrent Spark Declarative Pipelines, le cours offre une vue d'ensemble complète des composants fondamentaux tels que le traitement incrémental des données, les tables streaming, les vues matérialisées et les vues temporaires, en mettant en évidence leurs objectifs spécifiques et leurs différences.
Les sujets abordés comprennent:
• Le développement et le débogage de pipelines ETL avec l'éditeur multi-fichiers dans Spark Declarative Pipelines en utilisant SQL (avec des exemples de code Python fournis)
• La façon dont Spark Declarative Pipelines suit les dépendances des données dans un pipeline à travers le graphique du pipeline
• La configuration des ressources compute du pipeline, des actifs de données, des modes de déclencheur et d'autres options avancées
Ensuite, le cours présente les attentes en matière de qualité des données dans Spark Declarative Pipelines, guidant les utilisateurs à travers le processus d'intégration des attentes dans les pipelines pour valider et appliquer l'Intégrité des données. Les apprenants exploreront ensuite comment mettre un pipeline en production, notamment les options de planification, et l'activation de la journalisation des événements du pipeline pour surveiller la performance et l'état du pipeline.
Enfin, le cours explique comment implémenter le Change Data Capture (CDC) à l'aide de la syntaxe AUTO CDC INTO dans Spark Declarative Pipelines pour gérer les slowly changing dimensions (SCD Type 1 et Type 2), préparant ainsi les utilisateurs à intégrer le CDC dans leurs propres pipelines.
Remarque : Databricks Academy adopte progressivement un format basé sur des notebooks pour les sessions en salle de classe au sein de l'environnement Databricks, abandonnant l'utilisation de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de lab Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28145","entityUrl":{"path":"/fr/training/catalog/data-ingestion-with-lakeflow-connect-french-4447"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-ingestion-with-lakeflow-connect-french-4447"}}],"nid":28145,"vid":217450,"title":"Data Ingestion with Lakeflow Connect - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours propose une introduction complète à LakeFlow Connect, une solution évolutive et simplifiée pour l'Ingestion de données dans Databricks à partir d'un large éventail de sources. Vous commencerez par explorer les différents types de connecteurs LakeFlow Connect (Standard et Managed) et apprendrez diverses techniques d'Ingestion de données, notamment l'ingestion batch, batch incrémentielle et streaming. Vous passerez également en revue les principaux avantages de l'utilisation des tables Delta et de la Medallion Architecture.
Ensuite, vous développerez des compétences pratiques pour ingérer des données à partir d'un stockage d'objets cloud à l'aide des connecteurs Standard LakeFlow Connect. Cela inclut l'utilisation de méthodes telles que CREATE TABLE AS SELECT (CTAS), COPY INTO et Auto Loader, en mettant l'accent sur les avantages et les considérations propres à chaque approche. Vous apprendrez également comment ajouter des colonnes de métadonnées à vos tables de niveau Bronze lors de l'ingestion dans la Databricks Data Intelligence Platform. Le cours aborde ensuite la gestion des enregistrements qui ne correspondent pas au schéma de votre table à l'aide de la colonne de données récupérées, ainsi que les stratégies de gestion et d'analyse de ces données. Vous explorerez également des techniques pour ingérer et aplatir des données JSON semi-structurées.
Par la suite, vous découvrirez comment effectuer une Ingestion de données de niveau entreprise à l'aide des connecteurs Managed LakeFlow Connect pour intégrer des données provenant de bases de données et d'applications Software-as-a-Service (SaaS). Le cours présente également Partner Connect comme option d'intégration d'outils partenaires dans vos charges de travail d'ingestion.
Enfin, le cours se conclut par des stratégies d'ingestion alternatives, notamment les opérations MERGE INTO et l'exploitation du Databricks Marketplace, vous dotant ainsi de bases solides pour prendre en charge les cas d'usage modernes de data engineering.
Remarque : La Databricks Academy est en train de passer à un format basé sur des notebooks pour les sessions en classe au sein de l'environnement Databricks, en abandonnant l'utilisation de présentations de diapositives pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de laboratoire Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28206","entityUrl":{"path":"/fr/training/catalog/devops-essentials-for-data-engineering-french-4802"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/devops-essentials-for-data-engineering-french-4802"}}],"nid":28206,"vid":217511,"title":"DevOps Essentials for Data Engineering - French","price":"750.00","duration":14400,"body":{"processed":"Ce cours explore les meilleures pratiques d'ingénierie software et les principes DevOps, spécifiquement conçu pour les data engineers travaillant avec Databricks. Les participants développeront des bases solides dans des domaines clés tels que la qualité du code, le contrôle de version, la documentation et les tests. Le cours met l'accent sur le DevOps, en couvrant ses composantes essentielles, ses avantages et le rôle de l'intégration et de la livraison continues (CI/CD) dans l'optimisation des workflows de data engineering.
Vous apprendrez à appliquer les principes de modularité dans PySpark pour créer des composants réutilisables et structurer le code de manière efficace. La mise en pratique comprend la conception et l'implémentation de tests unitaires pour des fonctions PySpark à l'aide du Cadre pytest, suivies de tests d'intégration pour les data pipelines Databricks avec Spark Declarative Pipeline et Jobs afin de garantir leur fiabilité.
Le cours couvre également les opérations Git essentielles dans Databricks, notamment l'utilisation des Databricks Git Folders pour intégrer les pratiques d'intégration continue. Enfin, vous aurez un aperçu de haut niveau des différentes méthodes de déploiement des ressources Databricks, telles que REST API, CLI, SDK et Declarative Automation Bundles (DABs), vous fournissant ainsi les connaissances nécessaires pour déployer et gérer vos pipelines.
À l'issue du cours, vous maîtriserez les meilleures pratiques d'ingénierie software et de DevOps, vous permettant de construire des solutions de data engineering évolutives, maintenables et efficaces.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28219","entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-4897"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/deploy-workloads-with-lakeflow-jobs-french-4897"}}],"nid":28219,"vid":217524,"title":"Deploy Workloads with Lakeflow Jobs - French","price":"750.00","duration":14400,"body":{"processed":"Le cours Deploy Workloads with Lakeflow Jobs enseigne comment orchestrer et automatiser des workflows de données, d'analyse de données et d'IA à l'aide de Lakeflow Jobs en tant que plateforme d'orchestration unifiée au sein de l'écosystème Databricks.
• Vous apprendrez à concevoir et à mettre en œuvre des charges de travail de données à l'aide de graphes orientés acycliques (DAG), à configurer diverses options de planification et à implémenter des fonctionnalités avancées de workflow telles que l'exécution conditionnelle de tâches, les dépendances run-if et les boucles for each.
• Le cours couvre les bonnes pratiques pour créer des pipelines robustes et prêts pour la production, avec une sélection appropriée du compute, une orchestration modulaire, des techniques de gestion des erreurs et une conception tolérante aux pannes — le tout intégré nativement au sein de la Databricks Data Intelligence Platform.
Remarque : Databricks Academy passe à un format basé sur des cahiers de travail pour les sessions en présentiel au sein de l'environnement Databricks, et abandonne ainsi l'utilisation de présentations PowerPoint pour les cours magistraux. Vous pouvez accéder aux cahiers de travail des cours dans l'environnement de laboratoire Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28220","entityUrl":{"path":"/fr/training/catalog/data-engineering-with-databricks-french-4902"},"entityTranslations":[{"entityLanguage":{"id":"fr"},"entityUrl":{"path":"/fr/training/catalog/data-engineering-with-databricks-french-4902"}}],"nid":28220,"vid":217525,"title":"Data Engineering with Databricks - French","price":"1500.00","duration":57600,"body":{"processed":"Ce cours d'introduction constitue un point de départ approprié pour apprendre le Data Engineering avec Databricks.
Ci-dessous, nous décrivons chacun des quatre modules de quatre heures inclus dans ce cours.
Remarque : pour les quatre modules suivants, Databricks Academy adopte progressivement un format basé sur des notebooks pour les sessions en salle de classe au sein de l'environnement Databricks, abandonnant l'utilisation de diaporamas pour les cours. Vous pouvez accéder aux notebooks de cours dans l'environnement de lab Vocareum.
1. Data Ingestion with Lakeflow Connect
Ce cours offre une introduction complète à Lakeflow Connect, une solution évolutive et simplifiée pour ingérer des données dans Databricks à partir d'un large éventail de sources. Vous commencerez par explorer les différents types de connecteurs Lakeflow Connect (Standard et Managed) et découvrirez diverses techniques d'ingestion de données, notamment l'ingestion par batch, par batch incrémentiel et en streaming. Vous passerez également en revue les principaux avantages de l'utilisation de la Delta table et de l'architecture Medallion.
Ensuite, vous développerez des compétences pratiques pour ingérer des données depuis le cloud object storage à l'aide des Lakeflow Connect Standard Connectors. Cela inclut l'utilisation de méthodes telles que CREATE TABLE AS SELECT (CTAS), COPY INTO et Auto Loader, en mettant l'accent sur les avantages et les points à considérer de chaque approche. Vous apprendrez également à ajouter des colonnes de métadonnées à vos tables de niveau bronze lors de l'ingestion dans la Databricks Data Intelligence Platform. Le cours explique ensuite comment traiter les enregistrements qui ne correspondent pas au schema de votre table à l'aide de la colonne rescued data, ainsi que les stratégies de gestion et d'analyse de ces données. Vous explorerez aussi des techniques permettant d'ingérer et d'aplatir des données JSON semi-structurées.
Par la suite, vous découvrirez comment réaliser une ingestion de données de niveau entreprise à l'aide des Lakeflow Connect Managed Connectors afin d'importer des données depuis des bases de données et des applications Software-as-a-Service (SaaS). Le cours présente également Partner Connect comme une option pour intégrer des outils de partenaires à vos charges de travail d'ingestion.
Enfin, le cours se termine par des stratégies d'ingestion alternatives, notamment les opérations MERGE INTO et l'exploitation de Databricks Marketplace, vous dotant ainsi d'une base solide pour prendre en charge les cas d'usage modernes de data engineering.
2. Deploy Workloads with Lakeflow Jobs
Le cours Deploy Workloads with Lakeflow Jobs vous apprend à orchestrer et à automatiser les workflows de données, d'analytics et d'IA à l'aide de Lakeflow Jobs, une plateforme d'orchestration unifiée au sein de l'écosystème Databricks.
• Vous apprendrez à concevoir et à mettre en œuvre des charges de travail de données à l'aide de Directed Acyclic Graphs (DAGs), à configurer diverses options de planification et à implémenter des fonctionnalités de workflow avancées telles que l'exécution conditionnelle de tâches, les dépendances run-if et les boucles for each.
• Le cours couvre les bonnes pratiques pour créer des pipelines robustes et prêts pour la production, avec une sélection appropriée du compute, une orchestration modulaire, des techniques de gestion des erreurs et une conception tolérante aux pannes, le tout intégré nativement à la Databricks Data Intelligence Platform.
3. Build Data Pipelines with Apache Spark Declarative Pipelines
Ce cours présente aux utilisateurs les concepts et les compétences essentiels nécessaires à la création de pipelines de données à l'aide d'Apache Spark Declarative Pipelines (SDP) dans Databricks, pour l'ingestion et le traitement par batch incrémentiel ou en streaming via plusieurs streaming tables et materialized views. Conçu pour les data engineers qui débutent avec Spark Declarative Pipelines, le cours fournit une vue d'ensemble complète des composants principaux tels que le traitement incrémentiel des données, les streaming tables, les materialized views et les temporary views, en soulignant leurs objectifs spécifiques et leurs différences.
Les sujets abordés incluent :
• Le développement et le débogage de pipelines ETL avec l'éditeur multifichier de Spark Declarative Pipelines en SQL (des exemples de code Python sont fournis)
• La manière dont Spark Declarative Pipelines suit les dépendances de données dans un pipeline via le pipeline graph
• La configuration des ressources de compute du pipeline, des actifs de données, des modes de déclenchement et d'autres options avancées
Ensuite, le cours présente les data quality expectations dans Spark Declarative Pipelines et guide les utilisateurs tout au long du processus d'intégration des expectations aux pipelines afin de valider et de garantir l'intégrité des données. Les apprenants découvriront ensuite comment mettre un pipeline en production, y compris les options de planification, et comment activer la journalisation des événements du pipeline pour surveiller ses performances et son état de santé.
Enfin, le cours explique comment implémenter le Change Data Capture (CDC) à l'aide de la syntaxe AUTO CDC INTO dans Spark Declarative Pipelines pour gérer les slowly changing dimensions (SCD Type 1 et Type 2), préparant ainsi les utilisateurs à intégrer le CDC à leurs propres pipelines.
4. DevOps Essentials for Data Engineering
Ce cours explore les bonnes pratiques d'ingénierie logicielle et les principes DevOps, spécialement conçus pour les data engineers travaillant avec Databricks. Les participants acquerront une base solide sur des sujets clés tels que la qualité du code, le contrôle de version, la documentation et les tests. Le cours met l'accent sur le DevOps, en abordant ses composants principaux, ses avantages et le rôle de l'intégration et de la livraison continues (CI/CD) dans l'optimisation des workflows de data engineering.
Vous apprendrez à appliquer les principes de modularité dans PySpark afin de créer des composants réutilisables et de structurer le code de manière efficace. La pratique comprend la conception et la mise en œuvre de tests unitaires pour les fonctions PySpark à l'aide du framework pytest, suivies de tests d'intégration pour les pipelines de données Databricks avec Spark Declarative Pipeline et Jobs afin d'en garantir la fiabilité.
Le cours couvre également les opérations Git essentielles dans Databricks, y compris l'utilisation des Databricks Git Folders pour intégrer les pratiques d'intégration continue. Enfin, vous aurez un aperçu général des différentes méthodes de deployment des actifs Databricks, telles que REST API, CLI, SDK et Declarative Automation Bundles (DABs), ce qui vous permettra de maîtriser les techniques de déploiement et de gestion de vos pipelines.
À la fin du cours, vous maîtriserez les bonnes pratiques d'ingénierie logicielle et de DevOps, ce qui vous permettra de créer des solutions de data engineering évolutives, maintenables et efficaces.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]}]},"coursesES":{"entities":[{"id":"33991","entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-6637"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-6637"}}],"nid":33991,"vid":254514,"title":"Deploy Workloads with Lakeflow Jobs - Spanish","price":"0.00","duration":7200,"body":{"processed":"El curso Deploy Workloads with Lakeflow Jobs enseña cómo orquestar y automatizar flujos de trabajo de datos, analíticas e IA utilizando Lakeflow Jobs como plataforma de orquestación unificada dentro del ecosistema de Databricks.
• Aprenderá a diseñar e implementar cargas de trabajo de datos utilizando Grafos Acíclicos Dirigidos (DAGs), configurar diversas opciones de programación e implementar características avanzadas de flujos de trabajo, como la ejecución condicional de tareas, dependencias run-if y bucles for each.
• El curso abarca las mejores prácticas para crear Pipelines robustos y listos para producción con una selección adecuada de compute, orquestación modular, técnicas de manejo de errores y diseño tolerante a fallos, todo ello integrado nativamente en la Plataforma de Inteligencia de Datos de Databricks.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33993","entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-6639"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-6639"}}],"nid":33993,"vid":254516,"title":"Deploy Workloads with Lakeflow Jobs - Spanish","price":"75.00","duration":10800,"body":{"processed":"El curso Deploy Workloads with Lakeflow Jobs enseña cómo orquestar y automatizar flujos de trabajo de datos, analíticas e IA utilizando Lakeflow Jobs como plataforma de orquestación unificada dentro del ecosistema de Databricks.
• Aprenderá a diseñar e implementar cargas de trabajo de datos utilizando Grafos Acíclicos Dirigidos (DAGs), configurar diversas opciones de programación e implementar características avanzadas de flujos de trabajo, como la ejecución condicional de tareas, dependencias run-if y bucles for each.
• El curso abarca las mejores prácticas para crear Pipelines robustos y listos para producción con una selección adecuada de compute, orquestación modular, técnicas de manejo de errores y diseño tolerante a fallos, todo ello integrado nativamente en la Plataforma de Inteligencia de Datos de Databricks.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33957","entityUrl":{"path":"/es/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-spanish-6646"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-databricks-apps-with-genie-code-and-lakebase-spanish-6646"}}],"nid":33957,"vid":254347,"title":"Building Databricks Apps with Genie Code and Lakebase - Spanish","price":"750.00","duration":14400,"body":{"processed":"Databricks Apps permite crear e implementar aplicaciones interactivas de datos e IA directamente en la Plataforma de Databricks. Sin embargo, el desarrollo asistido por IA exitosamente va más allá de generar código: se trata de desarrollar un Flujo de trabajo efectivo.
En este curso práctico, crearás una Databricks App respaldada por Lakebase desde cero utilizando Genie Code como tu asistente de desarrollo de IA. A lo largo del camino, aprenderás un enfoque práctico y repetible para el desarrollo asistido por IA: especificar claramente la intención antes de generar código, trabajar en incrementos pequeños y verificables, aprovechar las Genie Code Skills reutilizables y tratar el resultado generado por IA como algo que se debe revisar y perfeccionar, no simplemente aceptar.
Crearás e implementarás una Databricks App, aprovisionarás y conectarás una base de datos Lakebase como su almacén transaccional, implementarás operaciones CRUD y utilizarás Genie Code para acelerar las tareas de desarrollo más comunes. Al finalizar el curso, no solo tendrás una aplicación funcional, sino también un Framework práctico para colaborar de manera efectiva con la IA en futuros proyectos de software.
Nota: Databricks Academy está haciendo la transición a un formato basado en notebooks para las sesiones presenciales dentro del entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33928","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6576"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6576"}}],"nid":33928,"vid":254188,"title":"Get Started with Databricks for Machine Learning - Spanish","price":"0.00","duration":7200,"body":{"processed":"En este curso, aprenderás las habilidades básicas que te permitirán utilizar la Plataforma de Inteligencia de Datos de Databricks para llevar a cabo un flujo de trabajo sencillo de ciencia de datos y machine learning. Se te ofrecerá un recorrido por el workspace y se te mostrará cómo trabajar con Notebooks. Explorarás el análisis exploratorio de datos y la ingeniería de características, realizarás seguimiento y administrarás modelos con MLflow, experimentarás utilizando Databricks Genie Code y desplegarás un modelo con Databricks Model Serving. Por último, el curso integra todas estas habilidades en un laboratorio integral que abarca el flujo de trabajo de machine learning de extremo a extremo.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33929","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6577"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6577"}}],"nid":33929,"vid":254189,"title":"Get Started with Databricks for Machine Learning - Spanish","price":"75.00","duration":10800,"body":{"processed":"En este curso, aprenderás las habilidades básicas que te permitirán utilizar la Plataforma de Inteligencia de Datos de Databricks para llevar a cabo un flujo de trabajo sencillo de ciencia de datos y machine learning. Se te ofrecerá un recorrido por el workspace y se te mostrará cómo trabajar con Notebooks. Explorarás el análisis exploratorio de datos y la ingeniería de características, realizarás seguimiento y administrarás modelos con MLflow, experimentarás utilizando Databricks Genie Code y desplegarás un modelo con Databricks Model Serving. Por último, el curso integra todas estas habilidades en un laboratorio integral que abarca el flujo de trabajo de machine learning de extremo a extremo.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"33884","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6582"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6582"}}],"nid":33884,"vid":253934,"title":"Get Started with Databricks for Generative AI - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso ofrece una introducción práctica a la Plataforma de Inteligencia de Datos de Databricks, con enfoque en sus componentes y características clave para construir e implementar sistemas de IA Generativa. Los participantes aprenderán cómo Databricks facilita el desarrollo de Soluciones de IA Generativa escalables y explorarán herramientas como AI Search, el Agent Framework y las capacidades de IA Generativa de MLflow para el seguimiento y registro de modelos. Este curso incluye experiencia práctica en la construcción y evaluación de Pipelines de Retrieval-Augmented Generation (RAG), la implementación de agentes de IA Generativa y el aprovechamiento de frameworks de evaluación para Optimizar el rendimiento. Al finalizar el curso, los participantes contarán con las habilidades necesarias para diseñar, implementar y monitorear aplicaciones comunes de IA Generativa en la Plataforma de Inteligencia de Datos de Databricks.
Languages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33885","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6583"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6583"}}],"nid":33885,"vid":253935,"title":"Get Started with Databricks for Generative AI - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso ofrece una introducción práctica a la Plataforma de Inteligencia de Datos de Databricks, con enfoque en sus componentes y características clave para construir e implementar sistemas de IA Generativa. Los participantes aprenderán cómo Databricks facilita el desarrollo de Soluciones de IA Generativa escalables y explorarán herramientas como AI Search, el Agent Framework y las capacidades de IA Generativa de MLflow para el seguimiento y registro de modelos. Este curso incluye experiencia práctica en la construcción y evaluación de Pipelines de Retrieval-Augmented Generation (RAG), la implementación de agentes de IA Generativa y el aprovechamiento de frameworks de evaluación para Optimizar el rendimiento. Al finalizar el curso, los participantes contarán con las habilidades necesarias para diseñar, implementar y monitorear aplicaciones comunes de IA Generativa en la Plataforma de Inteligencia de Datos de Databricks.
\nLanguages Available: English | 日本語 | Português BR | 한국어 | español | français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"33826","entityUrl":{"path":"/es/training/catalog/apache-spark-programming-with-databricks-spanish-6456"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/apache-spark-programming-with-databricks-spanish-6456"}}],"nid":33826,"vid":253494,"title":"Apache Spark Programming with Databricks - Spanish","price":"1500.00","duration":57600,"body":{"processed":"Este es un curso introductorio que sirve como un punto de entrada adecuado para aprender Apache Spark Programming with Databricks.
A continuación, describimos cada uno de los cuatro módulos de cuatro horas incluidos en este curso.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Introduction to Apache Spark
Este curso, diseñado para principiantes, cubre los fundamentos de Apache Spark para el procesamiento de datos a gran escala. Explorarás la arquitectura distribuida de Spark, dominarás la API de DataFrame y aprenderás a leer, escribir y procesar datos usando Python. A través de ejercicios prácticos, desarrollarás las habilidades necesarias para ejecutar transformaciones y acciones de Spark de manera eficiente.
Developing Applications with Apache Spark
Domina el procesamiento de datos escalable con Apache Spark en este curso. Aprende a construir Pipelines ETL eficientes, realizar analíticas avanzadas y optimizar transformaciones de datos distribuidas utilizando la DataFrame API de Spark. Explora agrupaciones, agregaciones, joins, operaciones de conjuntos y funciones de ventana. Trabaja con tipos de datos complejos como arrays, maps y structs mientras aplicas las mejores prácticas para la optimización del rendimiento.
Stream Processing and Analysis with Apache Spark
Este curso guía a los estudiantes sobre cómo desarrollar aplicaciones de procesamiento de transmisión escalables y tolerantes a fallos utilizando la API de Spark Structured Streaming en Databricks.
Monitoring and Optimizing Apache Spark Workloads on Databricks
Este curso cubre los componentes principales de la Plataforma de Databricks y Apache Spark con Delta Lake, con enfoque en la arquitectura Lakehouse, Unity Catalog y técnicas de Gestión de datos como Transacciones ACID y mantenimiento de tablas. Además, enseña a los estudiantes cómo optimizar el rendimiento de las consultas mediante particionamiento, shuffles y herramientas de ajuste, al mismo tiempo que utilizan el Spark UI para monitorear aplicaciones y resolver cuellos de botella.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33815","entityUrl":{"path":"/es/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-spanish-6557"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/monitoring-and-optimizing-apache-spark-workloads-on-databricks-spanish-6557"}}],"nid":33815,"vid":253366,"title":"Monitoring and Optimizing Apache Spark Workloads on Databricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso cubre los componentes principales de la Plataforma de Databricks y Apache Spark con Delta Lake, con enfoque en la arquitectura Lakehouse, Unity Catalog y técnicas de Gestión de datos como Transacciones ACID y mantenimiento de tablas. Además, enseña a los estudiantes cómo optimizar el rendimiento de las consultas mediante particionamiento, shuffles y herramientas de ajuste, al mismo tiempo que utilizan el Spark UI para monitorear aplicaciones y resolver cuellos de botella.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33809","entityUrl":{"path":"/es/training/catalog/stream-processing-and-analysis-with-apache-spark-spanish-6548"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/stream-processing-and-analysis-with-apache-spark-spanish-6548"}}],"nid":33809,"vid":253332,"title":"Stream Processing and Analysis with Apache Spark - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso guía a los estudiantes sobre cómo desarrollar aplicaciones de procesamiento de transmisión escalables y tolerantes a fallos utilizando la API de Spark Structured Streaming en Databricks.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 |한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33803","entityUrl":{"path":"/es/training/catalog/developing-applications-with-apache-spark-spanish-6533"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/developing-applications-with-apache-spark-spanish-6533"}}],"nid":33803,"vid":253308,"title":"Developing Applications with Apache Spark - Spanish","price":"750.00","duration":14400,"body":{"processed":"Domina el procesamiento de datos escalable con Apache Spark en este curso. Aprende a construir Pipelines ETL eficientes, realizar analíticas avanzadas y optimizar transformaciones de datos distribuidas utilizando la DataFrame API de Spark. Explora agrupaciones, agregaciones, joins, operaciones de conjuntos y funciones de ventana. Trabaja con tipos de datos complejos como arrays, maps y structs mientras aplicas las mejores prácticas para la optimización del rendimiento.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"33338","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6519"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6519"}}],"nid":33338,"vid":252745,"title":"Get Started with Databricks: End to End - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso es una introducción integral y práctica a la Plataforma de Inteligencia de Datos de Databricks. Seguirás un recorrido completo de principio a fin que comienza en el workspace y finaliza con una introducción a la IA y al machine learning, cubriendo las habilidades cotidianas que necesitas para trabajar con datos en Databricks.
El curso abarca:
Al finalizar el curso, te sentirás cómodo navegando por Databricks, encontrando y gobernando datos en Unity Catalog, escribiendo SQL y código en notebooks con asistencia de IA, creando dashboards y explorando datos con Genie.
Nota: para los archivos de lecciones SCORM, cierre la ventana de SCORM después de completar el contenido. No haga clic en el botón “Next Lesson”, ya que esto podría impedir que el módulo SCORM se marque como completado.
Languages Available : English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"33339","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6520"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6520"}}],"nid":33339,"vid":252746,"title":"Get Started with Databricks: End to End - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso es una introducción integral y práctica a la Plataforma de Inteligencia de Datos de Databricks. Seguirás un recorrido completo de principio a fin que comienza en el workspace y finaliza con una introducción a la IA y al machine learning, cubriendo las habilidades cotidianas que necesitas para trabajar con datos en Databricks.
El curso abarca:
Al finalizar el curso, te sentirás cómodo navegando por Databricks, encontrando y gobernando datos en Unity Catalog, escribiendo SQL y código en notebooks con asistencia de IA, creando dashboards y explorando datos con Genie.
Nota: para los archivos de lecciones SCORM, cierre la ventana de SCORM después de completar el contenido. No haga clic en el botón “Next Lesson”, ya que esto podría impedir que el módulo SCORM se marque como completado.
Languages Available : English | 日本語 | 한국어 | 普通话 | Português | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33329","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6493"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6493"}}],"nid":33329,"vid":252712,"title":"Get Started with Databricks Apps - Spanish","price":"0.00","duration":3600,"body":{"processed":"Este curso presenta Databricks Apps, una característica que permite a los desarrolladores crear e implementar aplicaciones de datos e IA seguras directamente en la Plataforma de Databricks. Está diseñado principalmente para Científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que las perspectivas de datos sean accesibles para usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de aplicaciones sencillas que se integran con un servicio externo, así como con un recurso de Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"33330","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6497"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6497"}}],"nid":33330,"vid":252713,"title":"Get Started with Databricks Apps - Spanish","price":"75.00","duration":7200,"body":{"processed":"Este curso presenta Databricks Apps, una característica que permite a los desarrolladores crear e implementar aplicaciones de datos e IA seguras directamente en la Plataforma de Databricks. Está diseñado principalmente para Científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que las perspectivas de datos sean accesibles para usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de aplicaciones sencillas que se integran con un servicio externo, así como con un recurso de Databricks.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"32113","entityUrl":{"path":"/es/training/catalog/ai-agent-fundamentals-accreditation-spanish-6471"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/ai-agent-fundamentals-accreditation-spanish-6471"}}],"nid":32113,"vid":251040,"title":"AI Agent Fundamentals Accreditation - Spanish","price":"0.00","duration":1800,"body":{"processed":"¡Bienvenido al cuestionario de acreditación sobre los fundamentos de los agentes de IA! En este cuestionario de 20 preguntas, evaluaremos sus conocimientos sobre los fundamentos de los agentes de IA, sus aplicaciones empresariales y cómo construirlos y desplegarlos utilizando Mosaic AI y Agent Bricks de Databricks. Tras completar correctamente el cuestionario, recibirá una insignia en un plazo de 48 horas a través de nuestro proveedor de insignias, Accredible. ¡Buena suerte!
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32080","entityUrl":{"path":"/es/training/catalog/databricks-fundamentals-spanish-3644"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/databricks-fundamentals-spanish-3644"}}],"nid":32080,"vid":250708,"title":"Databricks Fundamentals - Spanish","price":"0.00","duration":3600,"body":{"processed":"Este curso está diseñado para cualquiera que busque una introducción fundamental a Databricks y a la Plataforma de Inteligencia de Datos de Databricks. A lo largo de este curso, se le presentarán las diferentes características y productos que ofrece la plataforma y por qué estas funciones y productos son valiosos para todas las empresas que buscan aprovechar el poder de sus datos y activos de IA para acelerar su negocio.
Estos vídeos se proporcionan en un orden sugerido, pero usted puede verlos en el orden que prefiera. Además, le recomendamos ver todo el contenido en vídeo disponible antes de realizar la evaluación de acreditación de Databricks Fundamentals.
Tenga en cuenta que asumimos que usted no tiene conocimientos técnicos previos sobre Databricks ni plataformas de gestión de datos.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32081","entityUrl":{"path":"/es/training/catalog/databricks-fundamentals-accreditation-spanish-3664"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/databricks-fundamentals-accreditation-spanish-3664"}}],"nid":32081,"vid":250709,"title":"Databricks Fundamentals Accreditation - Spanish","price":"0.00","duration":1800,"body":{"processed":"Le damos la bienvenida a la Acreditación de Fundamentos de Databricks. En este cuestionario de 10 preguntas, evaluaremos sus conocimientos sobre la Plataforma de Inteligencia de Datos de Databricks. Al completar correctamente este cuestionario, recibirá una insignia (en un plazo de 48 horas) a través de nuestro proveedor de insignias, Accredible. ¡Le deseamos mucho éxito!
Languages Available: English | 日本語 | Português BR | 한국어 | Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"32064","entityUrl":{"path":"/es/training/catalog/machine-learning-with-databricks-spanish-6477"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/machine-learning-with-databricks-spanish-6477"}}],"nid":32064,"vid":250475,"title":"Machine Learning with Databricks - Spanish","price":"1500.00","duration":57600,"body":{"processed":"¡Le damos la bienvenida a Machine Learning with Databricks!
Este curso es su puerta de entrada para dominar los flujos de trabajo de machine learning en Databricks. Sumérjase en la preparación de datos, el desarrollo de modelos, el despliegue y las operaciones, con la guía de instructores expertos. Aprenda las habilidades esenciales para la exploración de datos, el entrenamiento de modelos y las estrategias de despliegue adaptadas a Databricks. Al finalizar el curso, contará con el conocimiento y la confianza para recorrer todo el ciclo de vida del machine learning en la Plataforma de Databricks, lo que le permitirá crear y desplegar soluciones de machine learning robustas de manera eficiente.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Data Preparation for Machine Learning
Este curso se centra en los fundamentos de la preparación de datos para machine learning utilizando Databricks. Los participantes aprenderán habilidades esenciales para explorar, limpiar y organizar datos adaptados para aplicaciones tradicionales de machine learning. Los temas clave incluyen visualización de datos, ingeniería de características y estrategias óptimas de almacenamiento de características. A través de ejercicios prácticos, los participantes adquirirán experiencia práctica en la preparación eficiente de conjuntos de datos para machine learning dentro de Databricks. Este curso está diseñado para Científicos de datos de nivel asociado y profesionales de machine learning, así como para personas que buscan mejorar su competencia en la preparación de datos, garantizando una base sólida para el despliegue exitosamente de Modelos de machine learning.
Machine Learning Model Development
Este completo curso ofrece una guía práctica para desarrollar modelos de machine learning tradicionales en Databricks, con énfasis en demostraciones prácticas y flujos de trabajo que utilizan las bibliotecas de ML más populares. Los participantes explorarán técnicas clave de ML, incluidas la regresión y el clustering, a la vez que aprovechan las potentes capacidades de Databricks. El curso abarca la integración de MLflow para el seguimiento de modelos, el Databricks Feature Store para la gestión de features y Optuna para el ajuste de hiperparámetros. Además, los participantes aprenderán a acelerar el desarrollo de modelos con Genie Code, el asistente de codificación impulsado por IA de Databricks que utiliza lenguaje natural, conexiones MCP, instrucciones y habilidades para guiar todo el ciclo de vida del ML. Al finalizar el curso, los alumnos contarán con habilidades prácticas y aplicables para desarrollar, optimizar e implementar modelos de machine learning de forma eficiente en el entorno de Databricks.
Machine Learning Model Deployment
Este curso está diseñado para presentar tres estrategias principales de despliegue de machine learning e ilustrar la implementación de cada estrategia en Databricks. Tras explorar los fundamentos del despliegue de modelos, el curso profundiza en la inferencia Batch, ofreciendo demostraciones prácticas y laboratorios para utilizar un modelo en escenarios de inferencia Batch, junto con consideraciones para la optimización del rendimiento. La segunda parte del curso cubre de manera exhaustiva el despliegue de Pipeline, mientras que el segmento final se centra en el despliegue en tiempo real. Los participantes realizarán demostraciones prácticas y laboratorios, desplegando modelos con Model Serving y utilizando el endpoint de servicio para inferencia en tiempo real.
Machine Learning Operations
Este curso guiará a los participantes a través de una exploración exhaustiva de las operaciones de Modelo de machine learning, con enfoque en MLOps y la gestión del ciclo de vida del modelo. El segmento inicial cubre los componentes esenciales de MLOps y las mejores prácticas, proporcionando a los participantes una base sólida para operacionalizar eficazmente los Modelos de machine learning. En la segunda parte del curso, profundizaremos en los fundamentos del ciclo de vida del modelo, demostrando cómo navegarlo de manera fluida utilizando el Registro de modelos en conjunto con Unity Catalog para una gestión eficiente del modelo. Al finalizar el curso, los participantes habrán adquirido perspectivas prácticas y una comprensión integral de los principios de MLOps, equipados con las habilidades necesarias para desenvolverse en el intrincado panorama de las operaciones de Modelo de machine learning.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"32059","entityUrl":{"path":"/es/training/catalog/ai-agent-fundamentals-spanish-6481"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/ai-agent-fundamentals-spanish-6481"}}],"nid":32059,"vid":250398,"title":"AI Agent Fundamentals - Spanish","price":"0.00","duration":5400,"body":{"processed":"Este curso fundamental presenta los agentes de IA y su uso en aplicaciones empresariales en Databricks, incluida la plataforma Mosaic AI y Agent Bricks. Los estudiantes examinarán qué son los agentes de IA, cómo funcionan y cómo imitan el razonamiento humano para gestionar tareas complejas.
El curso abarca casos de uso reales de agentes y ofrece una introducción básica a temas avanzados como los Flujos de trabajo agénticos y los sistemas multiagente. También explora cómo Agent Bricks simplifica el desarrollo de agentes listos para entornos empresariales en diversas aplicaciones, con demostraciones que muestran cómo construir y utilizar agentes en Databricks.
Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.
Languages Available: English | 日本語 | Português BR | 한국어
En este curso, aprenderá cómo implementar Gobernanza de datos a escala en Databricks utilizando Unity Catalog, con enfoque en el control de acceso basado en atributos, la observabilidad y el intercambio federado. Configurará ABAC con tags gobernados, migrará desde controles detallados heredados, habilitará y utilizará tablas del sistema para auditoría y monitoreo de costos, implementará Data Quality Monitoring para la calidad de datos y modelos, interpretará el Linaje para el impacto y cumplimiento, y aplicará gobernanza federada y patrones de Delta Sharing para una colaboración segura entre nubes.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"32040","entityUrl":{"path":"/es/training/catalog/generative-ai-fundamentals-spanish-4282"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/generative-ai-fundamentals-spanish-4282"}}],"nid":32040,"vid":250241,"title":"Generative AI Fundamentals - Spanish","price":"0.00","duration":7200,"body":{"processed":"La IA Generativa ha pasado de ser un experimento emergente a convertirse en una capacidad empresarial esencial, impulsando todo, desde el soporte inteligente al cliente hasta los agentes de IA que automatizan Flujos de trabajo complejos.
Las organizaciones que comprendan cómo implementarla de manera efectiva —basándose en sus propios datos y con una gobernanza orientada a la confianza— serán las que marquen el ritmo en sus Industrias. Sin embargo, con nuevos modelos que se lanzan semanalmente y capacidades que evolucionan rápidamente, saber cómo evaluar y Aplicar GenAI de forma estratégica importa más que perseguir el último lanzamiento. Ponte al día con los fundamentos de la IA Generativa —qué puede hacer, dónde aporta valor empresarial real y cómo implementarla de forma segura en Databricks— con este entrenamiento gratuito bajo demanda.
Languages Available: English | 日本語 | Português BR | 한국어 |Español | Français
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"32031","entityUrl":{"path":"/es/training/catalog/introduction-to-apache-spark-spanish-6459"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/introduction-to-apache-spark-spanish-6459"}}],"nid":32031,"vid":250180,"title":"Introduction to Apache Spark - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso, diseñado para principiantes, cubre los fundamentos de Apache Spark para el procesamiento de datos a gran escala. Explorarás la arquitectura distribuida de Spark, dominarás la API de DataFrame y aprenderás a leer, escribir y procesar datos usando Python. A través de ejercicios prácticos, desarrollarás las habilidades necesarias para ejecutar transformaciones y acciones de Spark de manera eficiente.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31914","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6452"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6452"}}],"nid":31914,"vid":249977,"title":"Get Started with Databricks for Data Warehousing - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso ofrece una descripción general completa y práctica del enfoque moderno de Databricks para el almacenamiento de datos, destacando cómo una arquitectura data lakehouse combina las fortalezas de los almacenes de datos tradicionales con la flexibilidad y escalabilidad de la nube. Trabajando de extremo a extremo con un minorista ficticio (Vintage Audio Co.), explorarás el workspace, realizarás consultas sobre tablas de Unity Catalog gobernadas, mantendrás las tablas administradas de Unity Catalog optimizadas para lecturas analíticas, cargarás datos de forma incremental con Auto Loader, modelarás un esquema en estrella y entregarás perspectivas consistentes a través de vistas de métricas de Unity Catalog — todo desde un único entorno gobernado, con características impulsadas por IA (Optimización Predictiva, Genie Code) integradas a lo largo del curso.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31913","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6451"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6451"}}],"nid":31913,"vid":249976,"title":"Get Started with Databricks for Data Warehousing - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso ofrece una descripción general completa y práctica del enfoque moderno de Databricks para el almacenamiento de datos, destacando cómo una arquitectura data lakehouse combina las fortalezas de los almacenes de datos tradicionales con la flexibilidad y escalabilidad de la nube. Trabajando de extremo a extremo con un minorista ficticio (Vintage Audio Co.), explorarás el workspace, realizarás consultas sobre tablas de Unity Catalog gobernadas, mantendrás las tablas administradas de Unity Catalog optimizadas para lecturas analíticas, cargarás datos de forma incremental con Auto Loader, modelarás un esquema en estrella y entregarás perspectivas consistentes a través de vistas de métricas de Unity Catalog — todo desde un único entorno gobernado, con características impulsadas por IA (Optimización Predictiva, Genie Code) integradas a lo largo del curso.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31870","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6403"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-end-to-end-spanish-6403"}}],"nid":31870,"vid":249483,"title":"Get Started with Databricks: End to End - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso es una introducción integral y práctica a la Plataforma de Inteligencia de Datos de Databricks. Seguirás un recorrido completo de principio a fin que comienza en el workspace y finaliza con una introducción a la IA y al machine learning, cubriendo las habilidades cotidianas que necesitas para trabajar con datos en Databricks.
El curso abarca:
• Navegar por el workspace de Databricks, las opciones de compute y las experiencias Lakehouse frente a Genie.
• Comprender e ingestar datos con Unity Catalog, incluyendo la subida de archivos y el Catalog Explorer.
• Trabajar en Databricks Notebooks y usar Genie Code para escribir y depurar código.
• Consultar datos con SQL, gestionar consultas guardadas y crear dashboards y visualizaciones.
• Explorar datos en lenguaje natural con Genie Agents.
• Una introducción a la IA y al machine learning con MLflow y el Data Science Agent.
Al finalizar el curso, te sentirás cómodo navegando por Databricks, encontrando y gobernando datos en Unity Catalog, escribiendo SQL y código en notebooks con asistencia de IA, creando dashboards y explorando datos con Genie.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"31818","entityUrl":{"path":"/es/training/catalog/machine-learning-operations-spanish-6377"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/machine-learning-operations-spanish-6377"}}],"nid":31818,"vid":248701,"title":"Machine Learning Operations - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso guiará a los participantes a través de una exploración exhaustiva de las operaciones de Modelo de machine learning, con enfoque en MLOps y la gestión del ciclo de vida del modelo. El segmento inicial cubre los componentes esenciales de MLOps y las mejores prácticas, proporcionando a los participantes una base sólida para operacionalizar eficazmente los Modelos de machine learning. En la segunda parte del curso, profundizaremos en los fundamentos del ciclo de vida del modelo, demostrando cómo navegarlo de manera fluida utilizando el Registro de modelos en conjunto con Unity Catalog para una gestión eficiente del modelo. Al finalizar el curso, los participantes habrán adquirido perspectivas prácticas y una comprensión integral de los principios de MLOps, equipados con las habilidades necesarias para desenvolverse en el intrincado panorama de las operaciones de Modelo de machine learning.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31798","entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-6371"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-6371"}}],"nid":31798,"vid":248567,"title":"Get Started with SQL Analytics and BI on Databricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta la Plataforma de Inteligencia de Datos de Databricks y las habilidades fundamentales que un analista de datos necesita para el trabajo diario de analíticas SQL y BI. Navegarás por el workspace y Unity Catalog, escribirás consultas SQL contra tablas administradas de Unity Catalog desde un Serverless SQL Warehouse, usarás Genie Code para generar y depurar SQL, trabajarás con Delta Lake (DML, historial de versiones, time travel y restauración), crearás y publicarás Dashboards de IA/BI, y crearás Agentes Genie para analíticas conversacionales.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31799","entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-6372"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-6372"}}],"nid":31799,"vid":248568,"title":"Get Started with SQL Analytics and BI on Databricks - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso presenta la Plataforma de Inteligencia de Datos de Databricks y las habilidades fundamentales que un analista de datos necesita para el trabajo diario de analíticas SQL y BI. Navegarás por el workspace y Unity Catalog, escribirás consultas SQL contra tablas administradas de Unity Catalog desde un Serverless SQL Warehouse, usarás Genie Code para generar y depurar SQL, trabajarás con Delta Lake (DML, historial de versiones, time travel y restauración), crearás y publicarás Dashboards de IA/BI, y crearás Agentes Genie para analíticas conversacionales.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"31103","entityUrl":{"path":"/es/training/catalog/data-modeling-strategies-spanish-6305"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/data-modeling-strategies-spanish-6305"}}],"nid":31103,"vid":246513,"title":"Data Modeling Strategies - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso guía a los profesionales a través del espectro completo de enfoques de modelado de datos en la Plataforma de Inteligencia de Datos de Databricks, desde técnicas clásicas de data warehouse (Inmon, Kimball, Data Vault 2.0), pasando por casos de uso de ML impulsados por Feature Store, hasta la comercialización de datos mediante Productos de Datos en Unity Catalog.
Cada enfoque de modelado se presenta con una clase teórica y se refuerza con una demostración práctica sobre un dataset compartido (muestras TPC-H). El curso finaliza con un laboratorio integral de extremo a extremo que abarca ERM, modelado dimensional, Data Vault 2.0 y el Feature Store en un único Flujo de trabajo integrado.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31092","entityUrl":{"path":"/es/training/catalog/machine-learning-model-deployment-spanish-6289"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/machine-learning-model-deployment-spanish-6289"}}],"nid":31092,"vid":246465,"title":"Machine Learning Model Deployment - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso está diseñado para presentar tres estrategias principales de despliegue de machine learning e ilustrar la implementación de cada estrategia en Databricks. Tras explorar los fundamentos del despliegue de modelos, el curso profundiza en la inferencia Batch, ofreciendo demostraciones prácticas y laboratorios para utilizar un modelo en escenarios de inferencia Batch, junto con consideraciones para la optimización del rendimiento. La segunda parte del curso cubre de manera exhaustiva el despliegue de Pipeline, mientras que el segmento final se centra en el despliegue en tiempo real. Los participantes realizarán demostraciones prácticas y laboratorios, desplegando modelos con Model Serving y utilizando el endpoint de servicio para inferencia en tiempo real.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31085","entityUrl":{"path":"/es/training/catalog/data-preparation-for-machine-learning-spanish-6284"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/data-preparation-for-machine-learning-spanish-6284"}}],"nid":31085,"vid":246444,"title":"Data Preparation for Machine Learning - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso se centra en los fundamentos de la preparación de datos para machine learning utilizando Databricks. Los participantes aprenderán habilidades esenciales para explorar, limpiar y organizar datos adaptados para aplicaciones tradicionales de machine learning. Los temas clave incluyen visualización de datos, ingeniería de características y estrategias óptimas de almacenamiento de características. A través de ejercicios prácticos, los participantes adquirirán experiencia práctica en la preparación eficiente de conjuntos de datos para machine learning dentro de Databricks. Este curso está diseñado para Científicos de datos de nivel asociado y profesionales de machine learning, así como para personas que buscan mejorar su competencia en la preparación de datos, garantizando una base sólida para el despliegue exitosamente de Modelos de machine learning.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"31050","entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-6064"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-6064"}}],"nid":31050,"vid":246147,"title":"Building Agentic Applications on Databricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso enseña a los participantes a crear aplicaciones de agentes listas para producción en Databricks. Aprenderán a crear herramientas de agentes gobernadas mediante Unity Catalog y MCP, a crear sistemas de uno o varios agentes con OpenAI Agents SDK y a aprovechar Agent Bricks y Genie en casos de uso de Knowledge Assistant orquestados con un agente supervisor. El curso abarca todo el proceso, desde la creación de prototipos de herramientas hasta la implementación en producción, con experiencia práctica en el uso de trazas de MLflow para observar la ejecución de agentes.
Nota: En los archivos de clase SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón “Siguiente lección”, ya que hacerlo puede impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31051","entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-6065"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-6065"}}],"nid":31051,"vid":246148,"title":"Building Agentic Applications on Databricks - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso enseña a los participantes a crear aplicaciones de agentes listas para producción en Databricks. Aprenderán a crear herramientas de agentes gobernadas mediante Unity Catalog y MCP, a crear sistemas de uno o varios agentes con OpenAI Agents SDK y a aprovechar Agent Bricks y Genie en casos de uso de Knowledge Assistant orquestados con un agente supervisor. El curso abarca todo el proceso, desde la creación de prototipos de herramientas hasta la implementación en producción, con experiencia práctica en el uso de trazas de MLflow para observar la ejecución de agentes.
Nota: En los archivos de clase SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón “Siguiente lección”, ya que hacerlo puede impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"31027","entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-6257"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-6257"}}],"nid":31027,"vid":246059,"title":"SQL Programming and Procedural Logic - Spanish","price":"0.00","duration":7200,"body":{"processed":"En este curso, explorará habilidades esenciales de programación SQL y lógica procedural en Databricks, centrándose en cómo crear flujos de trabajo analíticos modulares, mantenibles y listos para producción. Comenzará aprendiendo sobre construcciones SQL clave, como Common Table Expressions (incluidas CTE recursivas avanzadas), objetos con ámbito de sesión como vistas y tablas temporales, y User Defined Functions, que hacen que su desarrollo SQL sea más limpio y reutilizable. El curso luego lo guía a través de técnicas avanzadas de scripting SQL mediante instrucciones compuestas, variables, flujo de control, condicionales, bucles y manejo robusto de errores para crear procesos SQL estructurados y flexibles. También aprenderá a garantizar la consistencia de los datos en estos pipelines de varios pasos mediante transacciones de varias instrucciones compatibles con ACID. Por último, descubrirá cómo encapsular lógica en SQL Stored Procedures y orquestar flujos de trabajo complejos con Lakeflow Jobs y estrategias de migración, transformando tareas heredadas en pipelines modulares y automatizados que aprovechan todas las capacidades de la plataforma Databricks.
Nota: En el caso de los archivos de clase SCORM, cierre la ventana de SCORM después de completar el contenido. No haga clic en el botón ‘Next Lesson’, ya que esto puede impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"31028","entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-6258"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-6258"}}],"nid":31028,"vid":246060,"title":"SQL Programming and Procedural Logic - Spanish","price":"75.00","duration":10800,"body":{"processed":"En este curso, explorará habilidades esenciales de programación SQL y lógica procedural en Databricks, centrándose en cómo crear flujos de trabajo analíticos modulares, mantenibles y listos para producción. Comenzará aprendiendo sobre construcciones SQL clave, como Common Table Expressions (incluidas CTE recursivas avanzadas), objetos con ámbito de sesión como vistas y tablas temporales, y User Defined Functions, que hacen que su desarrollo SQL sea más limpio y reutilizable. El curso luego lo guía a través de técnicas avanzadas de scripting SQL mediante instrucciones compuestas, variables, flujo de control, condicionales, bucles y manejo robusto de errores para crear procesos SQL estructurados y flexibles. También aprenderá a garantizar la consistencia de los datos en estos pipelines de varios pasos mediante transacciones de varias instrucciones compatibles con ACID. Por último, descubrirá cómo encapsular lógica en SQL Stored Procedures y orquestar flujos de trabajo complejos con Lakeflow Jobs y estrategias de migración, transformando tareas heredadas en pipelines modulares y automatizados que aprovechan todas las capacidades de la plataforma Databricks.
Nota: En el caso de los archivos de clase SCORM, cierre la ventana de SCORM después de completar el contenido. No haga clic en el botón ‘Next Lesson’, ya que esto puede impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30897","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6205"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-apps-spanish-6205"}}],"nid":30897,"vid":245357,"title":"Get Started with Databricks Apps - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta Databricks Apps, una característica que permite a los desarrolladores crear e implementar aplicaciones de datos e IA seguras directamente en la Plataforma de Databricks. Está diseñado principalmente para Científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que las perspectivas de datos sean accesibles para usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de aplicaciones sencillas que se integran con un servicio externo, así como con un recurso de Databricks.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T11:00:00"},"timezone":"America/Chicago"}}]},{"id":"30888","entityUrl":{"path":"/es/training/catalog/automated-deployment-with-declarative-automation-bundles-spanish-6186"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/automated-deployment-with-declarative-automation-bundles-spanish-6186"}}],"nid":30888,"vid":245295,"title":"Automated Deployment with Declarative Automation Bundles - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso ofrece una revisión exhaustiva de los principios de DevOps y su aplicación a proyectos de Databricks. Comienza con una descripción general de los conceptos fundamentales de DevOps, DataOps, integración continua (CI), despliegue continuo (CD) y pruebas, y explora cómo estos principios pueden aplicarse a los Pipelines de Ingeniería de datos.
El curso se centra luego en el despliegue continuo dentro del proceso de CI/CD, examinando herramientas como la REST API, el SDK y el CLI de Databricks para el despliegue de proyectos. Aprenderás sobre los Declarative Automation Bundles (DABs) y cómo encajan en el proceso de CI/CD. Profundizarás en sus componentes clave, la estructura de carpetas y cómo agilizan el despliegue en diversos entornos de destino en Databricks. También aprenderás a añadir variables, modificar, validar, desplegar y ejecutar Declarative Automation Bundles para múltiples entornos con diferentes configuraciones mediante el CLI de Databricks.
Finalmente, el curso presenta Visual Studio Code como Entorno de Desarrollo Interactivo (IDE) para construir, probar y desplegar Declarative Automation Bundles de forma local, optimizando el proceso de desarrollo. El curso concluye con una introducción a la automatización de Pipelines de despliegue mediante GitHub Actions para mejorar el Flujo de trabajo de CI/CD con Declarative Automation Bundles.
Al finalizar este curso, estarás preparado para automatizar los despliegues de proyectos de Databricks con Declarative Automation Bundles, mejorando la eficiencia mediante las prácticas de DevOps.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30878","entityUrl":{"path":"/es/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-spanish-6184"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/advanced-techniques-with-apache-spark-declarative-pipelines-spanish-6184"}}],"nid":30878,"vid":245133,"title":"Advanced Techniques with Apache Spark Declarative Pipelines - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso explora Declarative Pipelines de Apache Spark de Databricks (SDP) para construir pipelines de transmisión de nivel de producción. Aprenderás patrones de diseño avanzados, aplicación robusta de calidad de datos e integración multiplataforma esenciales para la ingeniería de lakehouse en el mundo real.
A lo largo del curso, profundizarás en técnicas modernas de ingesta de datos y procesamiento, dominando herramientas como liquid clustering para la optimización del diseño y el patrón Multiplex Streaming para eventos con esquemas mixtos. Al finalizar los módulos, sabrás cómo manejar con confianza la evolución del esquema, automatizar change data capture (CDC) y garantizar la integridad de los datos.
A través de clases y demostraciones prácticas, podrás:
• Construir pipelines de múltiples flujos para ingestar datos de múltiples fuentes en una Tabla Bronce unificada.
• Aplicar liquid clustering y Expectativas de Calidad de Datos en las capas Plata y oro.
• Implementar el patrón Multiplex con Iceberg UniForm para el acceso a datos multiplataforma.
• Automatizar el seguimiento del historial SCD Tipo 2 mediante AUTO CDC INTO.
• Diseñar pipelines de cuarentena sin pérdida de datos para auditar y administrar registros no válidos.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2401,"name":"Professional"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30849","entityUrl":{"path":"/es/training/catalog/building-rag-agents-with-agent-bricks-spanish-6039"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-rag-agents-with-agent-bricks-spanish-6039"}}],"nid":30849,"vid":244642,"title":"Building RAG Agents with Agent Bricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso proporciona formación práctica para crear agentes de recuperación mediante Databricks Agent Bricks. Los participantes aprenderán a explorar y consultar Knowledge Assistants, convertir documentos no estructurados en datos estructurados mediante AI Functions, fragmentar texto para la recuperación semántica, crear índices de AI Search y crear Knowledge Assistants listos para producción respaldados por varias fuentes de conocimiento.
Nota: En los archivos de clase SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón “Siguiente lección”, ya que hacerlo puede impedir que el módulo SCORM se marque como completado.
Este curso de introducción presenta Databricks Lakebase, un servicio PostgreSQL Totalmente gestionado integrado en la Plataforma de Inteligencia de Datos de Databricks que acerca las cargas de trabajo operacionales (OLTP) y analíticas (OLAP).
El curso comienza con una lección conceptual que compara los sistemas OLTP y OLAP, explicando sus diferentes características de rendimiento, modelos de almacenamiento y casos de uso típicos. También explorarás los desafíos que enfrentan las organizaciones al mantener bases de datos transaccionales y plataformas analíticas separadas, incluyendo el movimiento de datos, la latencia y la complejidad arquitectónica.
A continuación, aprenderás cómo Databricks Lakebase ayuda a abordar estos desafíos proporcionando una base de datos operacional compatible con PostgreSQL que se integra directamente con el Databricks Lakehouse, permitiendo que las aplicaciones operacionales y las analíticas trabajen juntas dentro de una plataforma unificada.
A través de laboratorios prácticos, podrás:
Crear y explorar un proyecto de Lakebase utilizando compute con escalado automático
• Navegar por la interfaz de usuario de Lakebase, incluyendo ramificación, monitoreo y configuraciones
• Crear y consultar tablas utilizando el Editor SQL de Lakebase
• Consultar datos de Lakebase desde Databricks utilizando Lakehouse Federation y catálogos externos
• Realizar ETL inverso sincronizando tablas Delta con Lakebase
• Conectarse a Lakebase desde Python y realizar operaciones CRUD básicas
Este es un curso de introducción, por lo que el enfoque está en comprender los conceptos fundamentales y los flujos de trabajo básicos para trabajar con Lakebase. La construcción de aplicaciones completas en producción sobre Lakebase está fuera del alcance de este curso.
Al finalizar el curso, comprenderás cómo Lakebase permite a las organizaciones conectar los sistemas operacionales y las analíticas dentro de una única plataforma gobernada, impulsada por Unity Catalog y el Databricks Lakehouse.
Nota: En el caso de los archivos de clase SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo puede impedir que el módulo SCORM se marque como completado.
En este curso, aprenderá los conceptos básicos de la administración de la Plataforma de Inteligencia de Datos de Databricks. Ofrece una descripción general completa de Unity Catalog, un componente fundamental para una Gobernanza de datos eficaz en entornos de Databricks. Dividido en cinco módulos, comienza con una introducción detallada a la infraestructura de Databricks y su plataforma de inteligencia de datos, incluyendo un recorrido exhaustivo por el Workspace de Databricks. Explorará los principios de Gobernanza de datos dentro de Unity Catalog, abarcando sus conceptos clave, arquitectura y roles. El curso también hace énfasis en la gestión de metastores de Unity Catalog y recursos de compute, incluyendo clusters y almacenes SQL. Por último, dominará el control de acceso a los datos aprendiendo sobre privilegios, acceso detallado y cómo gobernar los objetos de datos. Al finalizar, contará con las habilidades esenciales para administrar Unity Catalog, implementar una Gobernanza de datos eficaz, optimizar los recursos de compute y aplicar estrategias sólidas de seguridad de datos. Con la adquisición de una suscripción a Databricks Labs, el curso también concluye con un ejercicio de laboratorio integral para practicar lo aprendido en un entorno real de Workspace de Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30761","entityUrl":{"path":"/es/training/catalog/get-started-with-data-governance-on-databricks-spanish-6138"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-data-governance-on-databricks-spanish-6138"}}],"nid":30761,"vid":243147,"title":"Get Started with Data Governance on Databricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"En este curso, explorará Unity Catalog y los controles de acceso detallados en Databricks con demostraciones prácticas y un laboratorio final. Aprenderá sobre los tipos de tabla, la configuración del catálogo y del esquema, la gestión de acceso basada en grupos y las estrategias de migración de controles de acceso. El curso incluye demostraciones sobre la aplicación de controles de acceso detallados con seguridad a nivel de fila y enmascaramiento de columnas, control de acceso basado en atributos, combinación de controles, migración de controles y un laboratorio para la implementación integral de la gobernanza.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-11-20T09:00:00"},"endDate":{"value":"2026-11-20T11:00:00"},"timezone":"America/Chicago"}}]},{"id":"30705","entityUrl":{"path":"/es/training/catalog/get-started-with-ai-agents-on-databricks-spanish-6127"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-ai-agents-on-databricks-spanish-6127"}}],"nid":30705,"vid":241205,"title":"Get Started with AI Agents on Databricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso es una introducción a los agentes de IA, su papel en las aplicaciones modernas de IA y cómo crear aplicaciones de agentes de IA en la Plataforma de Databricks. Aprenderás sobre los principios de los agentes de IA, cómo se diferencian de los sistemas de IA tradicionales y explorarás sus componentes clave. A través de demostraciones interactivas y laboratorios prácticos, verás cómo crear, implementar y evaluar agentes de IA en Databricks utilizando Databricks AI y Agent Bricks. Al finalizar este curso, comprenderás cómo crear e implementar agentes de IA utilizando la Plataforma de Databricks Data + AI.
Nota: Databricks Academy está realizando la transición a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, descontinuando el uso de presentaciones de diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-12-18T09:00:00"},"endDate":{"value":"2026-12-18T11:00:00"},"timezone":"America/Chicago"}}]},{"id":"30700","entityUrl":{"path":"/es/training/catalog/introduction-to-python-for-data-science-and-data-engineering-spanish-6117"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/introduction-to-python-for-data-science-and-data-engineering-spanish-6117"}}],"nid":30700,"vid":241179,"title":"Introduction to Python for Data Science and Data Engineering - Spanish","price":"1500.00","duration":57600,"body":{"processed":"Este curso está dirigido a personas sin ningún conocimiento previo de Python y proporciona los fundamentos de la interacción programática con datos. El curso comienza con una introducción básica a las expresiones de programación, variables y tipos de datos. Luego avanza hacia sentencias condicionales y de control, funciones, tipos de Colección, bucles, manejo de errores y clases. Aprenderás a extender Python con bibliotecas externas y adquirirás experiencia en el uso de la biblioteca Pandas para el análisis y la visualización de datos, incluyendo el escalado de Flujos de trabajo de Pandas con Apache Spark. Por último, explorarás los fundamentos de la computación en la nube. A lo largo del curso, adquirirás práctica mediante ejercicios de laboratorio, con recursos adicionales para profundizar en tu conocimiento de la programación después de la clase.
Nota: Databricks Academy está realizando la transición a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, descontinuando el uso de presentaciones de diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"30669","entityUrl":{"path":"/es/training/catalog/lakebase-app-integration-and-management-spanish-6103"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/lakebase-app-integration-and-management-spanish-6103"}}],"nid":30669,"vid":239095,"title":"Lakebase App Integration and Management - Spanish","price":"0.00","duration":7200,"body":{"processed":"En este curso, aprenderá a integrar Databricks Apps con Lakebase, la plataforma PostgreSQL totalmente gestionada y nativa de la nube de Databricks, para crear flujos de trabajo de aplicaciones seguros y listos para el uso empresarial. Partiendo de los conocimientos fundamentales sobre Databricks Apps y Lakebase, este curso se centra en los fundamentos de PostgreSQL, Lakebase Autoscaling, las prácticas seguras de SQL, la gestión segura de conexiones, el acceso basado en roles, la integración de la Data API y el desarrollo basado en ramas. También explorará cómo AppKit puede acelerar el desarrollo de aplicaciones dentro de este flujo de trabajo, ayudándole a pasar de los conceptos de integración a la implementación de forma más eficiente.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30670","entityUrl":{"path":"/es/training/catalog/lakebase-app-integration-and-management-spanish-6106"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/lakebase-app-integration-and-management-spanish-6106"}}],"nid":30670,"vid":239096,"title":"Lakebase App Integration and Management - Spanish","price":"75.00","duration":10800,"body":{"processed":"En este curso, aprenderá a integrar Databricks Apps con Lakebase, la plataforma PostgreSQL totalmente gestionada y nativa de la nube de Databricks, para crear flujos de trabajo de aplicaciones seguros y listos para el uso empresarial. Partiendo de los conocimientos fundamentales sobre Databricks Apps y Lakebase, este curso se centra en los fundamentos de PostgreSQL, Lakebase Autoscaling, las prácticas seguras de SQL, la gestión segura de conexiones, el acceso basado en roles, la integración de la Data API y el desarrollo basado en ramas. También explorará cómo AppKit puede acelerar el desarrollo de aplicaciones dentro de este flujo de trabajo, ayudándole a pasar de los conceptos de integración a la implementación de forma más eficiente.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"30643","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6097"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-machine-learning-spanish-6097"}}],"nid":30643,"vid":238902,"title":"Get Started with Databricks for Machine Learning - Spanish","price":"0.00","duration":7200,"body":{"processed":"En este curso, aprenderás habilidades básicas que te permitirán utilizar la Plataforma de Inteligencia de Datos de Databricks para llevar a cabo un flujo de trabajo sencillo de ciencia de datos y machine learning. Se te ofrecerá un recorrido por el workspace y se te mostrará cómo trabajar con Notebooks. Explorarás el análisis exploratorio de datos y la ingeniería de características, realizarás seguimiento y administrarás modelos con MLflow, experimentarás utilizando Databricks Genie Code y desplegarás un modelo con Databricks Model Serving. Por último, el curso integra todas estas habilidades en un laboratorio integral que abarca el flujo de trabajo de machine learning de extremo a extremo.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30614","entityUrl":{"path":"/es/training/catalog/lakehouse-architecture-fundamentals-spanish-6079"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/lakehouse-architecture-fundamentals-spanish-6079"}}],"nid":30614,"vid":238740,"title":"Lakehouse Architecture Fundamentals - Spanish","price":"0.00","duration":3600,"body":{"processed":"Un curso a nivel conceptual basado en The Data Lakehouse For Dummies. Lleva a los estudiantes desde \"no saber qué es un lakehouse\" hasta poder mantener una conversación fluida sobre la arquitectura lakehouse y las tecnologías que la sustentan: las limitaciones de las arquitecturas heredadas, qué es el lakehouse, sus tecnologías fundamentales y cómo habilita data intelligence y cargas de trabajo unificadas en Databricks.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2543,"name":"Introductory"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30616","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6081"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-warehousing-spanish-6081"}}],"nid":30616,"vid":238742,"title":"Get Started with Databricks for Data Warehousing - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso ofrece una descripción general completa y práctica del enfoque moderno de Databricks para el almacenamiento de datos, destacando cómo una arquitectura data lakehouse combina las fortalezas de los almacenes de datos tradicionales con la flexibilidad y escalabilidad de la nube. Trabajando de extremo a extremo con un minorista ficticio (Vintage Audio Co.), explorarás el workspace, realizarás consultas sobre tablas de Unity Catalog gobernadas, mantendrás las tablas administradas de Unity Catalog optimizadas para lecturas analíticas, cargarás datos de forma incremental con Auto Loader, modelarás un esquema en estrella y entregarás perspectivas consistentes a través de vistas de métricas de Unity Catalog — todo desde un único entorno gobernado, con características impulsadas por IA (Optimización Predictiva, Genie Code) integradas a lo largo del curso.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Languages Available: English | 日本語 | Português BR| 한국어
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30607","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6085"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-generative-ai-spanish-6085"}}],"nid":30607,"vid":238703,"title":"Get Started with Databricks for Generative AI - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso ofrece una introducción práctica a la Plataforma de Inteligencia de Datos de Databricks, con enfoque en sus componentes y características clave para construir e implementar sistemas de IA Generativa. Los participantes aprenderán cómo Databricks facilita el desarrollo de Soluciones de IA Generativa escalables y explorarán herramientas como AI Search, el Agent Framework y las capacidades de IA Generativa de MLflow para el seguimiento y registro de modelos. Este curso incluye experiencia práctica en la construcción y evaluación de Pipelines de Retrieval-Augmented Generation (RAG), la implementación de agentes de IA Generativa y el aprovechamiento de frameworks de evaluación para Optimizar el rendimiento. Al finalizar el curso, los participantes contarán con las habilidades necesarias para diseñar, implementar y monitorear aplicaciones comunes de IA Generativa en la Plataforma de Inteligencia de Datos de Databricks.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30443","entityUrl":{"path":"/es/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-spanish-6051"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-semantic-models-in-databricks-with-uc-metric-views-spanish-6051"}}],"nid":30443,"vid":237593,"title":"Building Semantic Models in Databricks with UC Metric Views - Spanish","price":"750.00","duration":14400,"body":{"processed":"En este curso, aprenderás cómo empoderar a tus consumidores de datos para obtener perspectivas de negocio validadas con menos carga para ti y el resto del equipo de datos e IA de tu empresa. A través de la construcción de una capa semántica sobre tu capa de oro, ofrecerás a los responsables de la toma de decisiones y a los analistas de negocio la oportunidad de explorar indicadores clave de rendimiento empresarial de nuevas formas, mientras se mantienen Operaciones de datos eficientes y Métricas validadas por la empresa.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2840,"name":"Data Warehousing Practitioner"}},"sessions":[]},{"id":"30416","entityUrl":{"path":"/es/training/catalog/answering-business-questions-with-databricks-genie-spanish-6022"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/answering-business-questions-with-databricks-genie-spanish-6022"}}],"nid":30416,"vid":237390,"title":"Answering Business Questions with Databricks Genie - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta Databricks Genie, una herramienta de análisis conversacional que le permite hacer preguntas en lenguaje sencillo sobre los datos de su organización y obtener respuestas gobernadas y seguras. Aprenderá qué es un Genie Space, cómo mantiene sus datos seguros y las mejores prácticas para obtener los mejores resultados. El curso termina con un juego práctico en el que usted competirá para investigar un misterio empresarial.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"30343","entityUrl":{"path":"/es/training/catalog/agent-evaluation-on-databricks-spanish-5999"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/agent-evaluation-on-databricks-spanish-5999"}}],"nid":30343,"vid":236792,"title":"Agent Evaluation on Databricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso enseña a los estudiantes a evaluar de forma sistemática agentes de IA utilizando el marco de evaluación de MLflow, abordando los desafíos particulares de los sistemas de IA no deterministas que las pruebas de software tradicionales no pueden manejar. Los estudiantes aprenden a implementar diversos enfoques de evaluación, incluidos jueces incorporados para criterios comunes como la corrección y la seguridad, jueces de directrices para requisitos específicos del negocio y jueces personalizados para necesidades especializadas. El curso abarca tanto la evaluación offline mediante datasets curados como el monitoreo online en producción, con experiencia práctica utilizando las capacidades de tracing de MLflow para comprender los patrones de ejecución de los agentes y recopilar comentarios humanos de distintos tipos de partes interesadas. A través de demostraciones prácticas y laboratorios, los estudiantes desarrollan habilidades para crear flujos de trabajo de evaluación que impulsan mejoras continuas de calidad a lo largo de todo el ciclo de vida del desarrollo de agentes de IA.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30319","entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-5995"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-agentic-applications-on-databricks-spanish-5995"}}],"nid":30319,"vid":236690,"title":"Building Agentic Applications on Databricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso enseña a los participantes a crear aplicaciones de agentes listas para producción en Databricks. Aprenderán a crear herramientas de agentes gobernadas mediante Unity Catalog y MCP, a crear sistemas de uno o varios agentes con OpenAI Agents SDK y a aprovechar Agent Bricks y Genie en casos de uso de Knowledge Assistant orquestados con un agente supervisor. El curso abarca todo el proceso, desde la creación de prototipos de herramientas hasta la implementación en producción, con experiencia práctica en el uso de trazas de MLflow para observar la ejecución de agentes.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30309","entityUrl":{"path":"/es/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-spanish-5974"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/deploying-and-monitoring-agent-applications-on-databricks-spanish-5974"}}],"nid":30309,"vid":236669,"title":"Deploying and Monitoring Agent Applications on Databricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso abarca el ciclo de vida completo de la implementación y el monitoreo de agentes de IA generativa en Databricks. Los participantes aprenderán a implementar agentes como Databricks Apps mediante Declarative Automation Bundles (DABs), integrar herramientas mediante Model Context Protocol (MCP), instrumentar agentes con MLflow Tracing y evaluar la calidad en producción mediante evaluadores, evaluadores de varios turnos y evaluación en línea. A través de demostraciones y laboratorios prácticos, los participantes obtendrán experiencia práctica en la creación, la observación y el monitoreo de agentes de IA listos para producción en la plataforma Databricks.
Nota: Databricks Academy está migrando a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, y deja de utilizar diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2404,"name":"Generative AI Engineer"}},"sessions":[]},{"id":"30304","entityUrl":{"path":"/es/training/catalog/building-rag-agents-with-agent-bricks-spanish-5964"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-rag-agents-with-agent-bricks-spanish-5964"}}],"nid":30304,"vid":236661,"title":"Building RAG Agents with Agent Bricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso proporciona formación práctica para crear agentes de recuperación mediante Databricks Agent Bricks. Los participantes aprenderán a explorar y consultar Knowledge Assistants, convertir documentos no estructurados en datos estructurados mediante AI Functions, fragmentar texto para la recuperación semántica, crear índices de AI Search y crear Knowledge Assistants listos para producción respaldados por varias fuentes de conocimiento.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29853","entityUrl":{"path":"/es/training/catalog/aibi-for-data-analysts-spanish-4249"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/aibi-for-data-analysts-spanish-4249"}}],"nid":29853,"vid":235516,"title":"AI/BI for Data Analysts - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso enseña a los analistas de datos a diseñar, crear, publicar y operar AI/BI Dashboards en Databricks. Los AI/BI Dashboards combinan datos gobernados por Unity Catalog con visualizaciones interactivas, filtros e integración con Genie, para que los usuarios de negocio puedan explorar respuestas sin escribir código.
El curso sigue una única implementación de extremo a extremo. Comienzas con tablas de origen en Unity Catalog y terminas con un dashboard de varias páginas publicado y supervisado. En el camino, aprenderás cómo los dashboards encajan en la familia de productos AI/BI de Databricks y dónde intervienen Genie, los conjuntos de datos, las visualizaciones y los filtros dentro del flujo de trabajo.
El contenido abarca:
• Los fundamentos de los AI/BI Dashboards y su relación con Genie y el resto de la plataforma Databricks.
• La exploración de los datos de origen en Unity Catalog y el diseño de conjuntos de datos reutilizables para dashboards con SQL.
• La creación de visualizaciones (KPIs, tendencias, desgloses) y el diseño de un dashboard de varias páginas bien estructurado.
• El uso de Genie Code para generar SQL, gráficos y filtros a partir de prompts en lenguaje natural.
• La incorporación de filtros para que los dashboards sean interactivos y respondan a las preguntas de quienes los consultan.
• La publicación, el uso compartido y la gestión de permisos para que las personas adecuadas puedan ver y editar el dashboard.
• La ejecución del dashboard en producción con actualización programada, almacenamiento en caché y supervisión del uso.
Al finalizar el curso, serás capaz de partir de una pregunta de negocio, diseñar los conjuntos de datos necesarios, crear un dashboard pulido y entregarlo a tu audiencia con los permisos correctos y una estrategia de actualización que lo mantenga preciso.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
Este curso enseña a los analistas de datos a diseñar, crear, publicar y operar AI/BI Dashboards en Databricks. Los AI/BI Dashboards combinan datos gobernados por Unity Catalog con visualizaciones interactivas, filtros e integración con Genie, para que los usuarios de negocio puedan explorar respuestas sin escribir código.
El curso sigue una única implementación de extremo a extremo. Comienzas con tablas de origen en Unity Catalog y terminas con un dashboard de varias páginas publicado y supervisado. En el camino, aprenderás cómo los dashboards encajan en la familia de productos AI/BI de Databricks y dónde intervienen Genie, los conjuntos de datos, las visualizaciones y los filtros dentro del flujo de trabajo.
El contenido abarca:
• Los fundamentos de los AI/BI Dashboards y su relación con Genie y el resto de la plataforma Databricks.
• La exploración de los datos de origen en Unity Catalog y el diseño de conjuntos de datos reutilizables para dashboards con SQL.
• La creación de visualizaciones (KPIs, tendencias, desgloses) y el diseño de un dashboard de varias páginas bien estructurado.
• El uso de Genie Code para generar SQL, gráficos y filtros a partir de prompts en lenguaje natural.
• La incorporación de filtros para que los dashboards sean interactivos y respondan a las preguntas de quienes los consultan.
• La publicación, el uso compartido y la gestión de permisos para que las personas adecuadas puedan ver y editar el dashboard.
• La ejecución del dashboard en producción con actualización programada, almacenamiento en caché y supervisión del uso.
Al finalizar el curso, serás capaz de partir de una pregunta de negocio, diseñar los conjuntos de datos necesarios, crear un dashboard pulido y entregarlo a tu audiencia con los permisos correctos y una estrategia de actualización que lo mantenga preciso.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"29843","entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5933"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5933"}}],"nid":29843,"vid":235300,"title":"Building Enterprise Applications with Databricks Apps - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso presenta Databricks Apps, una nueva funcionalidad que permite a los desarrolladores crear e implementar aplicaciones seguras de datos e IA directamente en la plataforma Databricks. Está pensado principalmente para científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que la información de los datos sea accesible para los usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de una aplicación sencilla que se integra con un servicio externo. A continuación, aprenderá a crear e implementar aplicaciones inteligentes y data-driven que se integran con las funcionalidades de la plataforma Databricks. Luego, el curso explica cómo desarrollar aplicaciones fuera del entorno de Databricks. Finaliza con un tratamiento detallado de las mejores prácticas para implementar aplicaciones empresariales seguras y confiables.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29844","entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5934"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5934"}}],"nid":29844,"vid":235301,"title":"Building Enterprise Applications with Databricks Apps - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta Databricks Apps, una nueva funcionalidad que permite a los desarrolladores crear e implementar aplicaciones seguras de datos e IA directamente en la plataforma Databricks. Está pensado principalmente para científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que la información de los datos sea accesible para los usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de una aplicación sencilla que se integra con un servicio externo. A continuación, aprenderá a crear e implementar aplicaciones inteligentes y data-driven que se integran con las funcionalidades de la plataforma Databricks. Luego, el curso explica cómo desarrollar aplicaciones fuera del entorno de Databricks. Finaliza con un tratamiento detallado de las mejores prácticas para implementar aplicaciones empresariales seguras y confiables.
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29800","entityUrl":{"path":"/es/training/catalog/catalog-management-and-data-organization-spanish-5935"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/catalog-management-and-data-organization-spanish-5935"}}],"nid":29800,"vid":234764,"title":"Catalog Management and Data Organization - Spanish","price":"750.00","duration":14400,"body":{"processed":"En este curso, aprenderás cómo diseñar, implementar y gobernar estructuras de catálogo y organización de datos a gran escala en la Databricks Data Intelligence Platform. Ofrece una vista comprensiva de Unity Catalog como la capa de gobernanza centralizada para un lakehouse empresarial. Dividido en cinco módulos, comienza ubicando Unity Catalog dentro del modelo de despliegue en nube — cubriendo el Account Console, creación de metastore y la jerarquía de roles de administrador. Luego traducirás topología organizacional (unidades de negocio, regiones y ambientes dev/QA/prod) en un diseño escalable de catálogo y esquema usando convenciones de nomenclatura, patrones de propiedad y delegación MANAGE. El curso luego cubre integración segura de almacenamiento con credenciales de almacenamiento, locaciones externas, la jerarquía de almacenamiento administrado, tablas administradas versus externas y UC Volumes para datos no tabulares. A continuación, aplicarás patrones de acceso y estrategias de aislamiento — la cadena GRANT de tres niveles, vinculación workspace-catálogo y políticas de Control de Acceso Basado en Atributos (ABAC) a nivel de esquema — para hacer cumplir protección de datos de grano fino a escala. Finalmente, el curso cierra con mejores prácticas para diseño de catálogo, automatización, permisos de menor privilegio y administración de acceso basada en grupos.
Nota: Databricks Academy está realizando la transición a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, descontinuando el uso de presentaciones de diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29789","entityUrl":{"path":"/es/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-spanish-5904"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/business-impact-accelerator-answering-business-questions-with-genie-spanish-5904"}}],"nid":29789,"vid":234736,"title":"Business Impact Accelerator: Answering Business Questions with Genie - Spanish","price":"0.00","duration":10800,"body":{"processed":"Este curso presenta Databricks Genie One, un entorno de trabajo colaborativo impulsado por IA diseñado en torno a sus necesidades y trabajo, donde puede hacer preguntas en lenguaje natural sobre los datos de su organización y obtener respuestas seguras y gobernadas, establecer cronogramas de informes para ejecutar automáticamente y automatizar su Flujo de trabajo para realizar más tareas de manera más rápida y precisa, ya que se basa en sus datos y negocio. Aprenderá qué son Genie, Genie One y los Agentes Genie, cómo mantienen sus datos seguros y las mejores prácticas para obtener los mejores resultados.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29781","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-4631"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-4631"}}],"nid":29781,"vid":234628,"title":"Get Started with Databricks for Data Engineering - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta las habilidades fundamentales necesarias para ejecutar un flujo de trabajo básico de ingeniería de datos en la Databricks Data Intelligence Platform. Explorará el área de trabajo, trabajará con Unity Catalog y aprenderá los componentes que un ingeniero de datos utiliza a diario en Databricks.
El curso sigue un enfoque práctico. Primero se familiarizará con el área de trabajo y, a continuación, avanzará con notebooks de Demo y Lab emparejados para cada tema. Las Demos le guían por un concepto con el instructor o un notebook guiado; los Labs le piden que aplique por su cuenta lo que acaba de ver.
El contenido abarca lo siguiente:
• La Databricks Data Intelligence Platform y cómo se integran el área de trabajo de Databricks, Unity Catalog y los notebooks.
• La creación y gestión de tablas Delta Lake.
• La modificación de datos con INSERT, UPDATE y DELETE.
• La exploración del historial de versiones y del time travel en tablas Delta.
• La ingesta de datos con las opciones de Lakeflow Connect: CTAS, la interfaz de carga (Upload UI) y COPY INTO.
• La creación de un pipeline de Arquitectura Medallion que transforma los datos a través de las capas Bronze, Silver y Gold.
• La automatización de pipelines con Lakeflow Jobs.
• (Bonus) La creación de un pipeline declarativo con Spark Declarative Pipelines.
Al finalizar el curso, se sentirá cómodo creando tablas Delta Lake, ingiriendo datos en ellas, transformando esos datos mediante un pipeline Medallion y automatizando todo el proceso como un job programado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29782","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-4632"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-4632"}}],"nid":29782,"vid":234629,"title":"Get Started with Databricks for Data Engineering - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso presenta las habilidades fundamentales necesarias para ejecutar un flujo de trabajo básico de ingeniería de datos en la Databricks Data Intelligence Platform. Explorará el área de trabajo, trabajará con Unity Catalog y aprenderá los componentes que un ingeniero de datos utiliza a diario en Databricks.
El curso sigue un enfoque práctico. Primero se familiarizará con el área de trabajo y, a continuación, avanzará con notebooks de Demo y Lab emparejados para cada tema. Las Demos le guían por un concepto con el instructor o un notebook guiado; los Labs le piden que aplique por su cuenta lo que acaba de ver.
El contenido abarca lo siguiente:
• La Databricks Data Intelligence Platform y cómo se integran el área de trabajo de Databricks, Unity Catalog y los notebooks.
• La creación y gestión de tablas Delta Lake.
• La modificación de datos con INSERT, UPDATE y DELETE.
• La exploración del historial de versiones y del time travel en tablas Delta.
• La ingesta de datos con las opciones de Lakeflow Connect: CTAS, la interfaz de carga (Upload UI) y COPY INTO.
• La creación de un pipeline de Arquitectura Medallion que transforma los datos a través de las capas Bronze, Silver y Gold.
• La automatización de pipelines con Lakeflow Jobs.
• (Bonus) La creación de un pipeline declarativo con Spark Declarative Pipelines.
Al finalizar el curso, se sentirá cómodo creando tablas Delta Lake, ingiriendo datos en ellas, transformando esos datos mediante un pipeline Medallion y automatizando todo el proceso como un job programado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"29758","entityUrl":{"path":"/es/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-spanish-3937"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/databricks-get-started-days-data-engineering-sql-analytics-and-bi-spanish-3937"}}],"nid":29758,"vid":234460,"title":"Databricks Get Started Days (Data Engineering + SQL Analytics and BI) - Spanish","price":"0.00","duration":14400,"body":{"processed":"Get Started with Databricks for Data Engineering
Este curso presenta las habilidades fundamentales necesarias para ejecutar un flujo de trabajo básico de ingeniería de datos en la Databricks Data Intelligence Platform. Explorará el área de trabajo, trabajará con Unity Catalog y aprenderá los componentes que un ingeniero de datos utiliza a diario en Databricks.
El curso sigue un enfoque práctico. Primero se familiarizará con el área de trabajo y, a continuación, avanzará con notebooks de Demo y Lab emparejados para cada tema. Las Demos le guían por un concepto con el instructor o un notebook guiado; los Labs le piden que aplique por su cuenta lo que acaba de ver.
Get Started with SQL Analytics and BI on Databricks
En este curso, aprenderá habilidades básicas que le permitirán utilizar la plataforma de inteligencia de datos Databricks para realizar un workflow de análisis de datos simple y respaldar esfuerzos de almacenamiento de datos.Se le brindará un recorrido por el workspace y se le mostrará cómo trabajar con objetos de datos en Databricks, como catálogos, esquemas, tablas, clústeres de cómputo, notebooks y dashboards.Luego, seguirás un workflow de análisis de datos básico para realizar tareas como manipular datos usando Databricks SQL, aprovechar los registros de versiones de Delta Lake para viajar en el tiempo, crear dashboards dentro de la plataforma y crear Genie Spaces para la exploración de datos utilizando indicaciones en lenguaje natural.También aprenderá cómo Databricks respalda las necesidades de almacenamiento de datos mediante el uso de Databricks SQL, Delta Live Tables y Unity Catalog.Con la compra de una suscripción a Databricks Labs, el curso también finaliza con un ejercicio de laboratorio para practicar lo aprendido en un entorno de workspace de Databricks en vivo.
Puedes crear una Databricks Free Edition account y probar las demostraciones paso a paso en un entorno práctico.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2026-09-25T13:00:00"},"endDate":{"value":"2026-09-25T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-10-28T13:00:00"},"endDate":{"value":"2026-10-28T17:00:00"},"timezone":"Europe/Paris"}},{"entity":{"startDate":{"value":"2026-11-25T09:00:00"},"endDate":{"value":"2026-11-25T13:00:00"},"timezone":"America/Chicago"}},{"entity":{"startDate":{"value":"2026-12-09T09:00:00"},"endDate":{"value":"2026-12-09T13:00:00"},"timezone":"America/Chicago"}},{"entity":{"startDate":{"value":"2027-01-27T09:00:00"},"endDate":{"value":"2027-01-27T13:00:00"},"timezone":"America/Chicago"}}]},{"id":"29751","entityUrl":{"path":"/es/training/catalog/machine-learning-model-development-spanish-5889"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/machine-learning-model-development-spanish-5889"}}],"nid":29751,"vid":234435,"title":"Machine Learning Model Development - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este completo curso ofrece una guía práctica para desarrollar modelos de machine learning tradicionales en Databricks, con énfasis en demostraciones prácticas y flujos de trabajo que utilizan las bibliotecas de ML más populares. Los participantes explorarán técnicas clave de ML, incluidas la regresión y el clustering, a la vez que aprovechan las potentes capacidades de Databricks. El curso abarca la integración de MLflow para el seguimiento de modelos, el Databricks Feature Store para la gestión de features y Optuna para el ajuste de hiperparámetros. Además, los participantes aprenderán a acelerar el desarrollo de modelos con Genie Code, el asistente de codificación impulsado por IA de Databricks que utiliza lenguaje natural, conexiones MCP, instrucciones y habilidades para guiar todo el ciclo de vida del ML. Al finalizar el curso, los alumnos contarán con habilidades prácticas y aplicables para desarrollar, optimizar e implementar modelos de machine learning de forma eficiente en el entorno de Databricks.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2400,"name":"Machine Learning Practitioner"}},"sessions":[]},{"id":"29636","entityUrl":{"path":"/es/training/catalog/get-started-with-lakebase-spanish-5883"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-lakebase-spanish-5883"}}],"nid":29636,"vid":234164,"title":"Get Started with Lakebase - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso de introducción presenta Databricks Lakebase, un servicio PostgreSQL Totalmente gestionado integrado en la Plataforma de Inteligencia de Datos de Databricks que acerca las cargas de trabajo operacionales (OLTP) y analíticas (OLAP).
El curso comienza con una lección conceptual que compara los sistemas OLTP y OLAP, explicando sus diferentes características de rendimiento, modelos de almacenamiento y casos de uso típicos. También explorarás los desafíos que enfrentan las organizaciones al mantener bases de datos transaccionales y plataformas analíticas separadas, incluyendo el movimiento de datos, la latencia y la complejidad arquitectónica.
A continuación, aprenderás cómo Databricks Lakebase ayuda a abordar estos desafíos proporcionando una base de datos operacional compatible con PostgreSQL que se integra directamente con el Databricks Lakehouse, permitiendo que las aplicaciones operacionales y las analíticas trabajen juntas dentro de una plataforma unificada.
A través de laboratorios prácticos, podrás:
Crear y explorar un proyecto de Lakebase utilizando compute con escalado automático
• Navegar por la interfaz de usuario de Lakebase, incluyendo ramificación, monitoreo y configuraciones
• Crear y consultar tablas utilizando el Editor SQL de Lakebase
• Consultar datos de Lakebase desde Databricks utilizando Lakehouse Federation y catálogos externos
• Realizar ETL inverso sincronizando tablas Delta con Lakebase
• Conectarse a Lakebase desde Python y realizar operaciones CRUD básicas
Este es un curso de introducción, por lo que el enfoque está en comprender los conceptos fundamentales y los flujos de trabajo básicos para trabajar con Lakebase. La construcción de aplicaciones completas en producción sobre Lakebase está fuera del alcance de este curso.
Al finalizar el curso, comprenderás cómo Lakebase permite a las organizaciones conectar los sistemas operacionales y las analíticas dentro de una única plataforma gobernada, impulsada por Unity Catalog y el Databricks Lakehouse.
Nota: En el caso de los archivos de clase SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo puede impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29617","entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-5828"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/sql-programming-and-procedural-logic-spanish-5828"}}],"nid":29617,"vid":234123,"title":"SQL Programming and Procedural Logic - Spanish","price":"750.00","duration":14400,"body":{"processed":"En este curso, explorará habilidades esenciales de programación SQL y lógica procedural en Databricks, centrándose en cómo crear flujos de trabajo analíticos modulares, mantenibles y listos para producción. Comenzará aprendiendo sobre construcciones SQL clave, como Common Table Expressions (incluidas CTE recursivas avanzadas), objetos con ámbito de sesión como vistas y tablas temporales, y User Defined Functions, que hacen que su desarrollo SQL sea más limpio y reutilizable. El curso luego lo guía a través de técnicas avanzadas de scripting SQL mediante instrucciones compuestas, variables, flujo de control, condicionales, bucles y manejo robusto de errores para crear procesos SQL estructurados y flexibles. También aprenderá a garantizar la consistencia de los datos en estos pipelines de varios pasos mediante transacciones de varias instrucciones compatibles con ACID. Por último, descubrirá cómo encapsular lógica en SQL Stored Procedures y orquestar flujos de trabajo complejos con Lakeflow Jobs y estrategias de migración, transformando tareas heredadas en pipelines modulares y automatizados que aprovechan todas las capacidades de la plataforma Databricks.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29447","entityUrl":{"path":"/es/training/catalog/building-reliable-conversational-agents-with-genie-spanish-5794"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-reliable-conversational-agents-with-genie-spanish-5794"}}],"nid":29447,"vid":232884,"title":"Building Reliable Conversational Agents with Genie - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso le enseña a diseñar, crear y mantener un Databricks Genie Space, una interfaz de lenguaje natural que permite a los usuarios de negocio formular preguntas sobre datos gobernados y obtener respuestas basadas en SQL sin necesidad de escribir código.
Aprenderá cómo se integra Genie en la familia de productos de IA/BI de Databricks y cómo traduce el lenguaje natural en consultas SQL fiables. El curso se centra en los aspectos clave para crear un Genie Space que ofrezca resultados precisos, coherentes y dignos de confianza.
Seguirá un flujo de trabajo integral, desde la comprensión de los datos de origen y la definición de puntos de referencia hasta la configuración y el perfeccionamiento de un Genie Space, utilizando el conjunto completo de herramientas de curación del Knowledge Store. Estas herramientas incluyen metadatos, sinónimos, coincidencia de prompts, lógica SQL, ejemplos de consultas e instrucciones de texto.
También aprenderá a compartir Genie Spaces con usuarios de negocio a través de Databricks One, a comprender cómo se aplica automáticamente la gobernanza de Unity Catalog y a utilizar la supervisión y los comentarios de los usuarios para mejorar continuamente la calidad a lo largo del tiempo.
Al finalizar el curso, será capaz de crear y gestionar un Genie Space listo para producción que ofrezca análisis conversacionales de autoservicio y gobernados a gran escala.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
En este curso, aprenderá a integrar Databricks Apps con Lakebase, la plataforma PostgreSQL totalmente gestionada y nativa de la nube de Databricks, para crear flujos de trabajo de aplicaciones seguros y listos para el uso empresarial. Partiendo de los conocimientos fundamentales sobre Databricks Apps y Lakebase, este curso se centra en los fundamentos de PostgreSQL, Lakebase Autoscaling, las prácticas seguras de SQL, la gestión segura de conexiones, el acceso basado en roles, la integración de la Data API y el desarrollo basado en ramas. También explorará cómo AppKit puede acelerar el desarrollo de aplicaciones dentro de este flujo de trabajo, ayudándole a pasar de los conceptos de integración a la implementación de forma más eficiente.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29371","entityUrl":{"path":"/es/training/catalog/get-started-with-lakebase-spanish-5673"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-lakebase-spanish-5673"}}],"nid":29371,"vid":231251,"title":"Get Started with Lakebase - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso de introducción presenta Databricks Lakebase, un servicio PostgreSQL Totalmente gestionado integrado en la Plataforma de Inteligencia de Datos de Databricks que acerca las cargas de trabajo operacionales (OLTP) y analíticas (OLAP).
El curso comienza con una lección conceptual que compara los sistemas OLTP y OLAP, explicando sus diferentes características de rendimiento, modelos de almacenamiento y casos de uso típicos. También explorarás los desafíos que enfrentan las organizaciones al mantener bases de datos transaccionales y plataformas analíticas separadas, incluyendo el movimiento de datos, la latencia y la complejidad arquitectónica.
A continuación, aprenderás cómo Databricks Lakebase ayuda a abordar estos desafíos proporcionando una base de datos operacional compatible con PostgreSQL que se integra directamente con el Databricks Lakehouse, permitiendo que las aplicaciones operacionales y las analíticas trabajen juntas dentro de una plataforma unificada.
Este es un curso de introducción, por lo que el enfoque está en comprender los conceptos fundamentales y los flujos de trabajo básicos para trabajar con Lakebase. La construcción de aplicaciones completas en producción sobre Lakebase está fuera del alcance de este curso.
Al finalizar el curso, comprenderás cómo Lakebase permite a las organizaciones conectar los sistemas operacionales y las analíticas dentro de una única plataforma gobernada, impulsada por Unity Catalog y el Databricks Lakehouse.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[{"entity":{"startDate":{"value":"2027-01-28T09:00:00"},"endDate":{"value":"2027-01-28T11:00:00"},"timezone":"America/Chicago"}}]},{"id":"29360","entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5630"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-enterprise-applications-with-databricks-apps-spanish-5630"}}],"nid":29360,"vid":230965,"title":"Building Enterprise Applications with Databricks Apps - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso presenta Databricks Apps, una nueva funcionalidad que permite a los desarrolladores crear e implementar aplicaciones seguras de datos e IA directamente en la plataforma Databricks. Está pensado principalmente para científicos de datos, ingenieros de datos y desarrolladores que necesitan crear aplicaciones personalizadas que hagan que la información de los datos sea accesible para los usuarios no técnicos dentro de sus organizaciones.
El curso comienza con una descripción general de los componentes principales de Databricks Apps, seguida de la implementación de una aplicación sencilla que se integra con un servicio externo. A continuación, aprenderá a crear e implementar aplicaciones inteligentes y data-driven que se integran con las funcionalidades de la plataforma Databricks. Luego, el curso explica cómo desarrollar aplicaciones fuera del entorno de Databricks. Finaliza con un tratamiento detallado de las mejores prácticas para implementar aplicaciones empresariales seguras y confiables.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | 한국어 | française | Português BR
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29311","entityUrl":{"path":"/es/training/catalog/building-etl-pipelines-with-sql-spanish-5608"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-etl-pipelines-with-sql-spanish-5608"}}],"nid":29311,"vid":229998,"title":"Building ETL Pipelines with SQL - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso enseña a crear pipelines ETL listos para producción utilizando exclusivamente SQL en la Databricks Data Intelligence Platform. Los participantes aprenden Streaming Tables con Auto Loader para la ingesta incremental, Materialized Views con actualización incremental para las transformaciones de Silver a Gold, AUTO CDC (FLOW AUTO CDC) para la gestión declarativa de dimensiones SCD Type 1 y Type 2, y Lakeflow Jobs con tareas SQL File para la orquestación en producción. El curso recorre un conjunto de datos retail realista a través de la arquitectura de medallón (Bronze → Silver → Gold).
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":false,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":null,"sessions":[]},{"id":"29312","entityUrl":{"path":"/es/training/catalog/building-etl-pipelines-with-sql-spanish-5612"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/building-etl-pipelines-with-sql-spanish-5612"}}],"nid":29312,"vid":229999,"title":"Building ETL Pipelines with SQL - Spanish","price":"75.00","duration":10800,"body":{"processed":"Este curso enseña a crear pipelines ETL listos para producción utilizando exclusivamente SQL en la Databricks Data Intelligence Platform. Los participantes aprenden Streaming Tables con Auto Loader para la ingesta incremental, Materialized Views con actualización incremental para las transformaciones de Silver a Gold, AUTO CDC (FLOW AUTO CDC) para la gestión declarativa de dimensiones SCD Type 1 y Type 2, y Lakeflow Jobs con tareas SQL File para la orquestación en producción. El curso recorre un conjunto de datos retail realista a través de la arquitectura de medallón (Bronze → Silver → Gold).
Nota: para los archivos de lección SCORM, asegúrese de cerrar la ventana de SCORM después de completar el contenido. No haga clic en el botón \"Next Lesson\", ya que hacerlo podría impedir que el módulo SCORM se marque como completado.
"},"includesLabs":true,"instructorLed":false,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2638,"name":"Paid & Subscription"}},"role":null,"sessions":[]},{"id":"29230","entityUrl":{"path":"/es/training/catalog/architecting-data-warehouses-for-large-scale-deployments-spanish-5501"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/architecting-data-warehouses-for-large-scale-deployments-spanish-5501"}}],"nid":29230,"vid":229439,"title":"Architecting Data Warehouses for Large-Scale Deployments - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso aborda la optimización del rendimiento, el control de costos y la seguridad para implementaciones de data warehousing a gran escala.
Este curso está dirigido a profesionales de data warehousing responsables de gestionar entornos de Databricks que dan servicio a cientos o miles de usuarios en múltiples unidades de negocio. Adquirirá las habilidades necesarias para escalar de forma eficiente las operaciones de data warehousing, manteniendo un alto rendimiento, la rentabilidad y el cumplimiento de los estándares de seguridad.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | française
Este curso enseña cómo construir pipelines ETL listos para producción utilizando SQL puro en la Plataforma de Inteligencia de Datos de Databricks. Los estudiantes aprenden Streaming Tables con Auto Loader para la ingesta incremental, Materialized Views con refrescar incremental para transformaciones de Plata a Oro, AUTO CDC (FLOW AUTO CDC) para la gestión declarativa de dimensiones SCD Tipo 1 y Tipo 2, y Declarative Pipelines de Apache Spark (SDP) para agrupar estos objetos en pipelines multi-tabla de producción con expectativas de calidad de datos, tablas PRIVATE y monitoreo unificado. El curso sigue un dataset minorista realista a través de la Arquitectura de Medallas (Bronce → Plata → Oro). La orquestación con Lakeflow Jobs está disponible como módulo adicional.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"29051","entityUrl":{"path":"/es/training/catalog/data-analysis-with-databricks-spanish-5314"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/data-analysis-with-databricks-spanish-5314"}}],"nid":29051,"vid":227988,"title":"Data Analysis with Databricks - Spanish","price":"1000.00","duration":28800,"body":{"processed":"Este curso ofrece una introducción completa a Databricks SQL. Los alumnos aprenderán a importar datos, escribir consultas, crear visualizaciones y paneles de control, y configurar alertas. Este curso te preparará para presentarte al examen de Certificación de Analista de Datos Asociado de Databricks.
Este curso consta de dos módulos de cuatro horas de duración.
SQL Analytics on Databricks
En este curso, aprenderá cómo usar Databricks de manera efectiva para el análisis de datos, con un enfoque específico en Databricks SQL. Como analista de datos Databricks, sus responsabilidades incluirán encontrar datos relevantes, analizarlo para aplicaciones potenciales y transformarlo en formatos que proporcionen valiosas perspectivas comerciales.
También comprenderá su papel en la gestión de objetos de datos y cómo manipularlos dentro de la Plataforma de Inteligencia de Datos de Databricks, utilizando herramientas como Notebooks, SQL Editor y Databricks SQL.
Además, aprenderá sobre la importancia de Unity Catalog en la gestión de activos de datos y la plataforma en general. Finalmente, el curso proporcionará una descripción general de cómo Databricks facilita la optimización del rendimiento y le enseñará cómo acceder a Query Insights para comprender los procesos que ocurren detrás de escena al ejecutar análisis de SQL en Databricks.
AI/BI for Data Analysts
Este curso enseña a los analistas de datos a diseñar, crear, publicar y operar AI/BI Dashboards en Databricks. Los AI/BI Dashboards combinan datos gobernados por Unity Catalog con visualizaciones interactivas, filtros e integración con Genie, para que los usuarios de negocio puedan explorar respuestas sin escribir código.
El curso sigue una única implementación de extremo a extremo. Comienzas con tablas de origen en Unity Catalog y terminas con un dashboard de varias páginas publicado y supervisado. En el camino, aprenderás cómo los dashboards encajan en la familia de productos AI/BI de Databricks y dónde intervienen Genie, los conjuntos de datos, las visualizaciones y los filtros dentro del flujo de trabajo.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어\n
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":null,"sessions":[]},{"id":"28078","entityUrl":{"path":"/es/training/catalog/aibi-for-data-analysts-spanish-4022"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/aibi-for-data-analysts-spanish-4022"}}],"nid":28078,"vid":217383,"title":"AI/BI for Data Analysts - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso enseña a los analistas de datos a diseñar, crear, publicar y operar AI/BI Dashboards en Databricks. Los AI/BI Dashboards combinan datos gobernados por Unity Catalog con visualizaciones interactivas, filtros e integración con Genie, para que los usuarios de negocio puedan explorar respuestas sin escribir código.
El curso sigue una única implementación de extremo a extremo. Comienzas con tablas de origen en Unity Catalog y terminas con un dashboard de varias páginas publicado y supervisado. En el camino, aprenderás cómo los dashboards encajan en la familia de productos AI/BI de Databricks y dónde intervienen Genie, los conjuntos de datos, las visualizaciones y los filtros dentro del flujo de trabajo.
El contenido abarca:
• Los fundamentos de los AI/BI Dashboards y su relación con Genie y el resto de la plataforma Databricks.
• La exploración de los datos de origen en Unity Catalog y el diseño de conjuntos de datos reutilizables para dashboards con SQL.
• La creación de visualizaciones (KPIs, tendencias, desgloses) y el diseño de un dashboard de varias páginas bien estructurado.
• El uso de Genie Code para generar SQL, gráficos y filtros a partir de prompts en lenguaje natural.
• La incorporación de filtros para que los dashboards sean interactivos y respondan a las preguntas de quienes los consultan.
• La publicación, el uso compartido y la gestión de permisos para que las personas adecuadas puedan ver y editar el dashboard.
• La ejecución del dashboard en producción con actualización programada, almacenamiento en caché y supervisión del uso.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28136","entityUrl":{"path":"/es/training/catalog/generative-ai-fundamentals-accreditation-spanish-4293"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/generative-ai-fundamentals-accreditation-spanish-4293"}}],"nid":28136,"vid":217441,"title":"Generative AI Fundamentals Accreditation - Spanish","price":"0.00","duration":900,"body":{"processed":"Bienvenido a la Fundamentos de IA Generativa de Databricks - Acreditación
Se trata de una evaluación de 20 minutos que pondrá a prueba sus conocimientos sobre conceptos fundamentales relacionados con la IA Generativa.
Después de completar con éxito esta evaluación, se le otorgará la insignia Databricks Generative AI Fundamentals.
Ruta de aprendizaje
• Esta acreditación forma parte del Plan de Aprendizaje Fundamentos de IA Generativa de Databricks.
Comprobante de finalización
• Con una tasa de aprobación del 80%, recibirá una insignia de Databricks.
Languages Available: English | 日本語 | Português BR | 한국어 | Español| française
Este curso ofrece una introducción completa a LakeFlow Connect, una solución escalable y simplificada para la ingesta de datos en Databricks desde una amplia variedad de fuentes. Comenzarás explorando los diferentes tipos de conectores de LakeFlow Connect (Standard y Managed) y aprenderás diversas técnicas de ingesta de datos, incluyendo ingesta Batch, incremental Batch y en transmisión. También revisarás los beneficios clave del uso de la Tabla Delta y la Arquitectura de Medallas.
A continuación, desarrollarás habilidades prácticas para la ingesta de datos desde almacenamiento de objetos en la nube utilizando los conectores estándar de LakeFlow Connect. Esto incluye trabajar con métodos como CREATE TABLE AS SELECT (CTAS), COPY INTO y Auto Loader, con énfasis en los beneficios y consideraciones de cada enfoque. También aprenderás cómo agregar columnas de metadatos a tus tablas de nivel Bronce durante la ingesta en la Plataforma de Inteligencia de Datos de Databricks. El curso también cubre cómo manejar registros que no coinciden con el esquema de tu tabla utilizando la columna de datos rescatados, junto con estrategias para gestionar y analizar estos datos. Asimismo, explorarás técnicas para la ingesta y el aplanamiento de datos JSON semiestructurados.
A continuación, explorarás cómo realizar la ingesta de datos a nivel empresarial utilizando los conectores administrados de LakeFlow Connect para incorporar datos desde bases de datos y aplicaciones de Software como servicio (SaaS). El curso también presenta Partner Connect como una opción para integrar herramientas de socios en tus cargas de trabajo de ingesta.
Finalmente, el curso concluye con estrategias alternativas de ingesta, incluyendo operaciones MERGE INTO y el aprovechamiento de Databricks Marketplace, proporcionándote una base sólida para dar soporte a casos de uso modernos de Ingeniería de datos.
Nota: Databricks Academy está realizando la transición a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, descontinuando el uso de presentaciones de diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de laboratorio de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28155","entityUrl":{"path":"/es/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-spanish-4495"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/build-data-pipelines-with-apache-spark-declarative-pipelines-spanish-4495"}}],"nid":28155,"vid":217460,"title":"Build Data Pipelines with Apache Spark™ Declarative Pipelines - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso presenta a los usuarios los conceptos y habilidades esenciales necesarios para construir pipelines de datos utilizando Apache Spark™ Declarative Pipelines (SDP) en Databricks para la ingesta y el procesamiento incremental por Batch o transmisión a través de múltiples tablas de transmisión y vistas materializadas. Diseñado para ingenieros de datos que son nuevos en Spark Declarative Pipelines, el curso ofrece una descripción general completa de los componentes principales, como el procesamiento incremental de datos, las tablas de transmisión, las vistas materializadas y las vistas temporales, destacando sus propósitos específicos y diferencias.
Los temas tratados incluyen:
• Desarrollo y depuración de pipelines ETL con el editor de múltiples archivos en Spark Declarative Pipelines usando SQL (con ejemplos de código en Python)
• Cómo Spark Declarative Pipelines rastrea las dependencias de datos en un pipeline a través del grafo del pipeline
• Configuración de recursos de compute del pipeline, activos de datos, modos de Trigger y otras opciones avanzadas
A continuación, el curso presenta las expectativas de calidad de datos en Spark Declarative Pipelines, guiando a los usuarios a través del proceso de integración de expectativas en los pipelines para validar y aplicar la Integridad de los datos. Los estudiantes explorarán cómo llevar un pipeline a producción, incluidas las opciones de programación y la habilitación del registro de eventos del pipeline para monitorear el rendimiento y el estado del pipeline.
Finalmente, el curso aborda cómo implementar Change Data Capture (CDC) utilizando la sintaxis AUTO CDC INTO dentro de Spark Declarative Pipelines para administrar slowly changing dimensions (SCD Tipo 1 y Tipo 2), preparando a los usuarios para integrar CDC en sus propios pipelines.
Nota: Databricks Academy está migrando a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, y dejará de usar diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de lab de Vocareum.
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28196","entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-4719"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/deploy-workloads-with-lakeflow-jobs-spanish-4719"}}],"nid":28196,"vid":217501,"title":"Deploy Workloads with Lakeflow Jobs - Spanish","price":"750.00","duration":14400,"body":{"processed":"El curso Deploy Workloads with Lakeflow Jobs enseña cómo orquestar y automatizar Flujos de trabajo de datos, analíticas e IA utilizando Lakeflow Jobs como plataforma de orquestación unificada dentro del ecosistema de Databricks.
• Aprenderás a diseñar e implementar cargas de trabajo de datos utilizando Grafos Acíclicos Dirigidos (DAGs), Configurar diversas opciones de programación e implementar características avanzadas de Flujos de trabajo, como la ejecución condicional de tareas, dependencias run-if y bucles for each.
• El curso cubre las mejores prácticas para crear Pipelines robustos y listos para producción con una selección adecuada de compute, orquestación modular, técnicas de manejo de errores y diseño tolerante a fallos, todo ello integrado nativamente en la Plataforma de Inteligencia de Datos de Databricks.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28197","entityUrl":{"path":"/es/training/catalog/data-engineering-with-databricks-spanish-4723"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/data-engineering-with-databricks-spanish-4723"}}],"nid":28197,"vid":217502,"title":"Data Engineering with Databricks - Spanish","price":"1500.00","duration":57600,"body":{"processed":"Este es un curso introductorio que sirve como un punto de entrada adecuado para aprender Data Engineering con Databricks.
A continuación, describimos cada uno de los cuatro módulos de cuatro horas incluidos en este curso.
Nota: para los siguientes cuatro módulos, Databricks Academy está migrando a un formato basado en notebooks para las sesiones en el aula dentro del entorno de Databricks, y dejará de usar diapositivas para las clases. Puede acceder a los notebooks de las clases en el entorno de lab de Vocareum.
1. Data Ingestion with Lakeflow Connect
Este curso ofrece una introducción integral a Lakeflow Connect, una solución escalable y simplificada para ingerir datos en Databricks desde una amplia variedad de fuentes. Comenzará explorando los diferentes tipos de conectores de Lakeflow Connect (Standard y Managed) y aprenderá diversas técnicas de ingesta de datos, incluidas la ingesta por batch, batch incremental y streaming. También repasará los principales beneficios de usar la Delta table y la arquitectura Medallion.
A continuación, desarrollará habilidades prácticas para ingerir datos desde cloud object storage utilizando los Lakeflow Connect Standard Connectors. Esto incluye trabajar con métodos como CREATE TABLE AS SELECT (CTAS), COPY INTO y Auto Loader, con énfasis en los beneficios y las consideraciones de cada enfoque. También aprenderá a agregar columnas de metadatos a sus tablas de nivel bronze durante la ingesta en la Databricks Data Intelligence Platform. Luego, el curso aborda cómo gestionar los registros que no coinciden con el schema de su tabla mediante la columna rescued data, junto con estrategias para administrar y analizar estos datos. También explorará técnicas para ingerir y aplanar datos JSON semiestructurados.
Después de esto, explorará cómo realizar una ingesta de datos de nivel empresarial utilizando los Lakeflow Connect Managed Connectors para incorporar datos desde bases de datos y aplicaciones Software-as-a-Service (SaaS). El curso también presenta Partner Connect como una opción para integrar herramientas de partners en sus cargas de trabajo de ingesta.
Por último, el curso concluye con estrategias de ingesta alternativas, incluidas las operaciones MERGE INTO y el aprovechamiento de Databricks Marketplace, lo que le proporcionará una base sólida para respaldar casos de uso modernos de data engineering.
2. Deploy Workloads with Lakeflow Jobs
El curso Deploy Workloads with Lakeflow Jobs enseña a orquestar y automatizar flujos de trabajo de datos, analytics e IA utilizando Lakeflow Jobs como una plataforma de orquestación unificada dentro del ecosistema de Databricks.
• Aprenderá a diseñar e implementar cargas de trabajo de datos mediante Directed Acyclic Graphs (DAGs), a configurar diversas opciones de programación y a implementar funciones avanzadas de flujo de trabajo, como la ejecución condicional de tareas, las dependencias run-if y los bucles for each.
• El curso abarca las prácticas recomendadas para crear pipelines robustos y listos para producción, con una selección adecuada de compute, orquestación modular, técnicas de manejo de errores y un diseño tolerante a fallos, todo ello integrado de forma nativa en la Databricks Data Intelligence Platform.
3. Build Data Pipelines with Apache Spark Declarative Pipelines
Este curso presenta a los usuarios los conceptos y las habilidades esenciales necesarios para crear pipelines de datos utilizando Apache Spark Declarative Pipelines (SDP) en Databricks para la ingesta y el procesamiento por batch incremental o streaming a través de múltiples streaming tables y materialized views. Diseñado para data engineers que se inician en Spark Declarative Pipelines, el curso ofrece una descripción general integral de componentes esenciales como el procesamiento incremental de datos, las streaming tables, las materialized views y las temporary views, y destaca sus propósitos específicos y sus diferencias.
Los temas tratados incluyen:
• Desarrollo y depuración de pipelines de ETL con el editor multiarchivo de Spark Declarative Pipelines usando SQL (se proporcionan ejemplos de código en Python)
• Cómo Spark Declarative Pipelines rastrea las dependencias de datos en un pipeline a través del pipeline graph
• Configuración de los recursos de compute del pipeline, los activos de datos, los modos de activación y otras opciones avanzadas
A continuación, el curso presenta las data quality expectations en Spark Declarative Pipelines, y guía a los usuarios a través del proceso de integración de expectations en los pipelines para validar y hacer cumplir la integridad de los datos. Luego, los alumnos explorarán cómo poner un pipeline en producción, incluidas las opciones de programación, y cómo habilitar el registro de eventos del pipeline para supervisar su rendimiento y su estado.
Por último, el curso aborda cómo implementar Change Data Capture (CDC) mediante la sintaxis AUTO CDC INTO en Spark Declarative Pipelines para gestionar slowly changing dimensions (SCD Type 1 y Type 2), lo que prepara a los usuarios para integrar CDC en sus propios pipelines.
4. DevOps Essentials for Data Engineering
Este curso explora las prácticas recomendadas de ingeniería de software y los principios de DevOps, diseñados específicamente para data engineers que trabajan con Databricks. Los participantes construirán una base sólida en temas clave como la calidad del código, el control de versiones, la documentación y las pruebas. El curso hace hincapié en DevOps, y abarca sus componentes esenciales, sus beneficios y el papel de la integración y entrega continuas (CI/CD) en la optimización de los flujos de trabajo de data engineering.
Aprenderá a aplicar principios de modularidad en PySpark para crear componentes reutilizables y estructurar el código de manera eficiente. La experiencia práctica incluye diseñar e implementar pruebas unitarias para funciones de PySpark utilizando el framework pytest, seguidas de pruebas de integración para pipelines de datos de Databricks con Spark Declarative Pipeline y Jobs a fin de garantizar la fiabilidad.
El curso también abarca operaciones esenciales de Git en Databricks, incluido el uso de las Databricks Git Folders para integrar prácticas de integración continua. Por último, obtendrá una visión general de alto nivel de los diversos métodos de deployment de activos de Databricks, como REST API, CLI, SDK y Declarative Automation Bundles (DABs), lo que le proporcionará el conocimiento de las técnicas para desplegar y administrar sus pipelines.
Al finalizar el curso, dominará las prácticas recomendadas de ingeniería de software y DevOps, lo que le permitirá crear soluciones de data engineering escalables, fáciles de mantener y eficientes.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28209","entityUrl":{"path":"/es/training/catalog/devops-essentials-for-data-engineering-spanish-4822"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/devops-essentials-for-data-engineering-spanish-4822"}}],"nid":28209,"vid":217514,"title":"DevOps Essentials for Data Engineering - Spanish","price":"750.00","duration":14400,"body":{"processed":"Este curso explora las mejores prácticas de ingeniería de software y los principios de DevOps, diseñado específicamente para ingenieros de datos que trabajan con Databricks. Los participantes desarrollarán una base sólida en temas clave como la calidad del código, el control de versiones, la documentación y las pruebas. El curso hace énfasis en DevOps, abarcando sus componentes principales, sus beneficios y el papel de la integración y entrega continuas (CI/CD) en la optimización de los flujos de trabajo de Ingeniería de datos.
Aprenderás a aplicar principios de modularidad en PySpark para crear componentes reutilizables y estructurar el código de manera eficiente. La experiencia práctica incluye el diseño e implementación de pruebas unitarias para funciones de PySpark utilizando el Framework pytest, seguido de pruebas de integración para Pipelines de datos de Databricks con Spark Declarative Pipeline y Jobs para garantizar la fiabilidad.
El curso también cubre las operaciones esenciales de Git dentro de Databricks, incluyendo el uso de Databricks Git Folders para integrar prácticas de integración continua. Por último, realizarás una revisión de alto nivel de los distintos métodos de implementación para los activos de Databricks, como REST API, CLI, SDK y Declarative Automation Bundles (DABs), proporcionándote el conocimiento de las técnicas necesarias para implementar y administrar tus Pipelines.
Al finalizar el curso, tendrás dominio de las mejores prácticas de ingeniería de software y DevOps, lo que te permitirá construir Soluciones de Ingeniería de datos escalables, mantenibles y eficientes.
Nota: Databricks Academy está pasando a un formato basado en cuadernos para las sesiones presenciales en el entorno de Databricks, dejando de utilizar presentaciones de diapositivas para las clases. Puedes acceder a los cuadernos de las clases en el entorno de laboratorio de Vocareum.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2403,"name":"Data Engineer"}},"sessions":[]},{"id":"28221","entityUrl":{"path":"/es/training/catalog/sql-analytics-on-databricks-spanish-4922"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/sql-analytics-on-databricks-spanish-4922"}}],"nid":28221,"vid":217526,"title":"SQL Analytics on Databricks - Spanish","price":"750.00","duration":14400,"body":{"processed":"En este curso, aprenderá cómo usar Databricks de manera efectiva para el análisis de datos, con un enfoque específico en Databricks SQL. Como analista de datos Databricks, sus responsabilidades incluirán encontrar datos relevantes, analizarlo para aplicaciones potenciales y transformarlo en formatos que proporcionen valiosas perspectivas comerciales.
También comprenderá su papel en la gestión de objetos de datos y cómo manipularlos dentro de la Plataforma de Inteligencia de Datos de Databricks, utilizando herramientas como Notebooks, SQL Editor y Databricks SQL.
Además, aprenderá sobre la importancia de Unity Catalog en la gestión de activos de datos y la plataforma en general. Finalmente, el curso proporcionará una descripción general de cómo Databricks facilita la optimización del rendimiento y le enseñará cómo acceder a Query Insights para comprender los procesos que ocurren detrás de escena al ejecutar análisis de SQL en Databricks.
Languages Available: English | 日本語 | Português BR | 한국어
"},"includesLabs":true,"instructorLed":true,"type":[{"entity":{"tid":2441,"name":"ILT PAID: Customer"}}],"skillLevel":{"entity":{"tid":2399,"name":"Associate"}},"cost":{"entity":{"tid":2397,"name":"Paid"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[]},{"id":"28418","entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-3728"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-sql-analytics-and-bi-on-databricks-spanish-3728"}}],"nid":28418,"vid":217723,"title":"Get Started with SQL Analytics and BI on Databricks - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta la Plataforma de Inteligencia de Datos de Databricks y las habilidades fundamentales que un analista de datos necesita para el trabajo diario de analíticas SQL y BI. Navegarás por el workspace y Unity Catalog, escribirás consultas SQL contra tablas administradas de Unity Catalog desde un Serverless SQL Warehouse, usarás Genie Code para generar y depurar SQL, trabajarás con Delta Lake (DML, historial de versiones, time travel y restauración), crearás y publicarás Dashboards de IA/BI, y crearás Agentes Genie para analíticas conversacionales.
Puede crear una cuenta de Databricks Free Edition y probar las demostraciones guiadas en un entorno práctico.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
"},"includesLabs":false,"instructorLed":true,"type":[{"entity":{"tid":2396,"name":"Academy"}}],"skillLevel":{"entity":{"tid":2406,"name":"Onboarding"}},"cost":{"entity":{"tid":2405,"name":"Free"}},"role":{"entity":{"tid":2402,"name":"Data Analyst"}},"sessions":[{"entity":{"startDate":{"value":"2026-10-21T14:00:00"},"endDate":{"value":"2026-10-21T16:00:00"},"timezone":"Europe/Paris"}}]},{"id":"28438","entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-3908"},"entityTranslations":[{"entityLanguage":{"id":"es"},"entityUrl":{"path":"/es/training/catalog/get-started-with-databricks-for-data-engineering-spanish-3908"}}],"nid":28438,"vid":217743,"title":"Get Started with Databricks for Data Engineering - Spanish","price":"0.00","duration":7200,"body":{"processed":"Este curso presenta las habilidades fundamentales necesarias para ejecutar un flujo de trabajo básico de ingeniería de datos en la Databricks Data Intelligence Platform. Explorará el área de trabajo, trabajará con Unity Catalog y aprenderá los componentes que un ingeniero de datos utiliza a diario en Databricks.
El curso sigue un enfoque práctico. Primero se familiarizará con el área de trabajo y, a continuación, avanzará con notebooks de Demo y Lab emparejados para cada tema. Las Demos le guían por un concepto con el instructor o un notebook guiado; los Labs le piden que aplique por su cuenta lo que acaba de ver.
El contenido abarca lo siguiente:
• La Databricks Data Intelligence Platform y cómo se integran el área de trabajo de Databricks, Unity Catalog y los notebooks.
• La creación y gestión de tablas Delta Lake.
• La modificación de datos con INSERT, UPDATE y DELETE.
• La exploración del historial de versiones y del time travel en tablas Delta.
• La ingesta de datos con las opciones de Lakeflow Connect: CTAS, la interfaz de carga (Upload UI) y COPY INTO.
• La creación de un pipeline de Arquitectura Medallion que transforma los datos a través de las capas Bronze, Silver y Gold.
• La automatización de pipelines con Lakeflow Jobs.
• (Bonus) La creación de un pipeline declarativo con Spark Declarative Pipelines.
Languages Available: English | 日本語 | Português BR | 한국어 | Español | française
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