Pre-requisites and Course Syllabus先决条件与课程大纲

This mini-course is intended to be a follow-on to the Python for Data Science, AI and Development course for you to demonstrate basic Python skills that you have acquired in that course.
本迷你课程旨在作为“Python for Data Science, AI and Development”课程的后续课程，让您展示在该课程中获得的基本 Python 技能。

In this mini-course, you will be assuming the role of a Data Engineer. In this role, you will be given a scenario and dataset to begin your Python code creation. During this process, you will perform specific tasks such as extracting data from different file formats, collecting data through APIs and web scraping and finally transforming the collected data into a ready-to-load format. You will then submit your Python notebook and screenshots for your peers to review and evaluate your work.
在本迷你课程中，您将扮演数据工程师的角色。在此角色中，您将获得一个场景和数据集，以开始创建 Python 代码。在此过程中，您将执行特定任务，例如从不同的文件格式中提取数据，通过 API 和网络抓取收集数据，最后将收集到的数据转换为可加载的格式。然后，您将提交 Python 笔记本和屏幕截图，供同行审阅和评估您的工作。

To be successful in completing this project, you should have already completed the Python for Data Science, AI, and Development course or have equivalent skills for working with Data and Python.
要成功完成此项目，您应该已经完成了“Python for Data Science, AI, and Development”课程，或者具备处理数据和 Python 的同等技能。

Module 1: Extract, Transform, Load
模块 1：提取、转换、加载

• Lesson 0: Welcome  第 0 课：欢迎
• Lesson 1: Working with Python Using an IDE
  第 1 课：使用 IDE 进行 Python 编程
• Lesson 2: Extract, Transform, Load (ETL)
  第 2 课：提取、转换、加载 (ETL)
• Lesson 3: Access Data Using Web Scraping and APIs
  第 3 课：使用网络抓取和 API 访问数据
• Lesson 4: Accessing and Loading Databases using Python
  第 4 课：使用 Python 访问和加载数据库
• Lesson 5: Module Summary and Assessment
  第 5 课：模块总结与评估

Module 2: Final Project  模块 2：最终项目

• Lesson 1: Graded Final Project
  第 1 课：评分最终项目
• Lesson 2: Course Wrap-Up  第 2 课：课程总结

Module 3: Python Coding practices and Packaging Concepts (optional)
模块 3：Python 编码实践和打包概念（可选）

• Lesson 1: Application Development and Packaging using Python
  第 1 课：使用 Python 进行应用程序开发和打包