Introduction to Python for Data Science and Data Engineering - Mandarin Chinese

本课程专为 Python 零基础学员设计，旨在介绍以编程方式处理数据的基础知识。课程从编程表达式、变量和数据类型的基本介绍开始，随后逐步深入讲解条件语句与控制语句、函数、集合类型、循环、错误处理以及类。您将学习如何通过外部依赖库扩展 Python 的功能，并获得使用 Pandas 依赖库进行数据分析与可视化的实践经验，包括借助 Apache Spark 扩展 Pandas 工作流。最后，您将浏览云计算的基本原理。在整个课程中，您将通过实验室练习获得大量实践机会，并可参考额外的资源，在课后进一步深化编程知识。

Skill Level

Introductory

Duration

10h

Prerequisites

本内容是为具备以下技能、知识和能力的参与者而开发的：

• 基本的计算机使用能力及对操作系统的熟悉程度（文件管理、网络浏览器、软件安装）

• 对数学概念的初步理解（算术运算、基础代数、统计学基础）

• 对数据概念的初步了解（数据集、表格、行、列、数据类型）

• 熟悉网络浏览器和在线学习平台，以便访问 Databricks 工作区

• 具备基本的问题解决能力和逻辑思维，用于理解编程概念

• 无需具备 Python 使用经验；对其他编程语言中编程概念的一般性了解将有所帮助

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Data Engineer

Introduction to Python for Data Science and Data Engineering

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.

Automated Deployment with Declarative Automation Bundles - Mandarin Chinese

本课程全面介绍了 DevOps 原则及其在 Databricks 项目中的应用。课程首先概述了核心 DevOps、DataOps、持续集成（CI）、持续部署（CD）和测试的基本概念，并探讨了如何将这些原则应用于数据工程管道。

课程随后聚焦于 CI/CD 流程中的持续部署，介绍用于项目部署的工具，包括 Databricks REST API、SDK 和 CLI。您将了解声明式自动化包（DAB）及其在 CI/CD 流程中的作用，深入学习其关键组件、文件夹结构，以及它们如何简化在 Databricks 中跨各种目标环境的部署流程。您还将学习如何使用 Databricks CLI 为多个具有不同配置的环境添加变量、修改、验证、部署和执行声明式自动化包。

最后，课程介绍如何将 Visual Studio Code 作为交互式开发环境（IDE），用于在本地构建、测试和部署声明式自动化包，从而优化开发流程。课程最后介绍如何使用 GitHub Actions 自动化部署管道，以增强声明式自动化包的 CI/CD 工作流。

完成本课程后，您将具备使用声明式自动化包自动化 Databricks 项目部署的能力，并能够通过 DevOps 实践提升工作效率。

注意：

Databricks Academy 正在将所有自定进度课程从视频讲座转为更简洁的 PDF 格式，其中包含幻灯片和讲义。请注意，演示视频仍将以原始格式提供。我们非常希望听到您对这一变化的看法，因此请通过课程末尾的课程调查分享您的反馈。感谢您成为我们学习社区的一员！本课程是 ‘Advanced Data Engineering with Databricks’ 系列的第四门课程。

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Lab

Professional

Building RAG Agents with Agent Bricks

This course provides hands-on training for building retrieval agents on Databricks. Participants will learn to create Genie Agents for unstructured data, perform information retrieval with Lakebase Search, parse and transform unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, and build AI Search indexes with multiple search modes.

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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Lab

Associate