Get Started with Databricks for Machine Learning - Mandarin Chinese

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

Skill Level

Onboarding

Duration

Prerequisites

本内容面向具备以下技能/知识/能力的学员而开发：
• 对 Python 有初级水平的了解。

• 对 DS/ML 概念（例如分类模型和回归模型）、常见的模型指标（例如 F1-score）以及 Python 库（例如 scikit-learn 和 XGBoost）有基本的了解。

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Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Monitoring and Observability with System Tables

Comprehensive auditing, monitoring, and observability using system tables, query history analysis, and proactive alerting for DBSQL environments.

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.

Free

Associate

Lakebase Architecture Deep Dive

Opens the hood on Lakebase. Built on the lecture-demo pattern (teach a concept, immediately run it), the course explains the compute/storage split, why it yields a ~5x write gain by eliminating Full Page Writes, how copy-on-write branching is an O(1) operation, and how the five-level object hierarchy organizes real deployments. It is the architectural foundation the rest of the Lakebase pathway builds on.

Free

Associate

Data Warehousing Practitioner

Building Semantic Models in Databricks with UC Metric Views

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.

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

Free

Associate