Engineering setup for AI & Data Products

Foundations for Setting Up AI and Data Products

Learn the core engineering foundations required to set up AI and data products properly:

1. Terminal Basics * Navigating folders and files * Running commands and scripts * Understanding terminal state, paths, and tree output 2. Python Project Anatomy * Organizing folders and files * Separating source code, notebooks, configs, tests, and documentation * Understanding what belongs where in a real project 3. Python Package Boundaries * Structuring Python modules and packages * Separating reusable code from one-off scripts * Managing imports cleanly 4. Virtual Environments and Dependency Management * Creating isolated environments * Managing dependencies with uv * Keeping project setups reproducible 5. Configuration Hygiene * Separating code from environment-specific settings * Using config files and environment variables properly * Avoiding hardcoded paths, keys, and credentials 6. Git and GitHub * Tracking code changes * Creating commits and branches * Working with remote repositories * Understanding basic collaboration workflows 7. Secrets Management * Storing API keys and credentials safely * Using .env files correctly * Preventing secrets from being committed to Git 8. Repository Visibility * Understanding public, private, and internal repositories * Knowing when a project should or should not be public * Managing access safely 9. Licenses * Understanding why licenses matter * Knowing the difference between common open-source licenses * Choosing the right license for personal, client, or commercial projects 10. Testing and Project Checks * Running basic project checks * Using pytest for starter backend validation * Checking work before commits and pull requests 11. FastAPI Starter App and Local Services * Creating a minimal FastAPI app * Adding a health endpoint * Understanding ports, processes, logs, Docker, Compose, and Postgres as a local service 12. README, Makefile, and Guided Project * Documenting setup clearly * Creating stable project commands * Completing a guided starter-repo project