Welcome to the Python AI Engineering course repository.
This repository contains course materials for the Python for AI engineering course (see the public site: https://pythonforai.piatripathi.ca/). The course is organized into 12 pillars that cover foundational to advanced topics in Python and practical AI engineering workflows. Each pillar contains examples, labs, a project prompt, and solutions.
Structure
- requirements.txt — pinned/primary dependencies for examples and labs
- .gitignore — recommended Python ignores
- LICENSE — MIT license (Priyamvada Tripathi)
- pillar-01/ ... pillar-12/ — each pillar contains:
- examples/ — small, focused example scripts and notebooks
- labs/ — lab exercises for students
- project/ — a project specification or larger assignment
- solutions/ — instructor solutions (kept here for convenience)
- README.md — describes the pillar scope and learning outcomes
Course site
How to use this repo
- Clone or download the repository.
- Create a virtual environment: python -m venv .venv
- Activate it and install dependencies: pip install -r requirements.txt
- Explore pillars in order (pillar-01 → pillar-12)
- Use pytest to run tests included with some labs and examples.
Contributing
- If you want to propose changes or new content, please open an issue or a PR following repository contribution guidelines.
License
- MIT — see LICENSE file for full text.