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.

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.

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.

Module 1: Extract, Transform, Load

• Lesson 0: Welcome

• Lesson 1: Working with Python Using and IDE

• Lesson 2: Extract, Transform, Load (ETL)

• Lesson 3: Access Data Using Web Scraping and APIs

• Lesson 4: Accessing and Loading Databases using Python

• Lesson 5: Module Summary and Assessment

Module 2: Final Project

• Lesson 1: Graded Final Project

• Lesson 2: Course Wrap-Up

Module 3: Python Coding practices and Packaging Concepts (optional)

• Lesson 1: Application Development and Packaging using Python