Book Content
chapters • 16h4m total length
1. Preparing the workspace
2. First Steps in coding variables and data types
3. Functions
4. Data Structures
5. Loops and other compound statements
6. First script: Geocoding with Web APIs
7. Scraping Data from the Web with Beautiful Soup 4
8. Simulation with Classes and inheritance
9. Shell, Git, Conda, and More at Your Command
10. Python for Data Applications
11. Data cleaning and manipulation
12. Data Exploration and Visualization
13. Training a Machine Learning model
14. Improving your Models Metrics pipelines and experiments
15. Packaging and testing with poetry and pytest
16. Data Pipelines with Luigi
17. Lets build a dashboard
18. Serving models with Rest API
19. Serverless API using Chalice
20. Best practices and Python performance
