Python for AI-Driven Automation & Business Data Science

From your first line of Python to shipping a real AI-driven automation — a hands-on curriculum (self-paced or instructor-led) across Python fluency, business data science, machine learning, deep learning, AI engineering, and production.

The arc of the course, from Foundations through Data Science, Machine Learning, Deep Learning, AI Engineering and Agents & MCP, to Production.
  • 119 runnable notebooks
  • 20 modules
  • 300+ exercises
  • 326 in-lesson checkpoints
  • 100% offline

This site is the reference documentation for the course: one section per module (the module guides, plus the full mini-book chapters for CI/CD, Django, and Containers & Docker), together with the fast track, quizzes, and dataset guides. The notebooks themselves live in the GitHub repository — every notebook link on this site takes you straight to it, and each one can be opened in Google Colab with one click.

Where to start

  • New to the course? Start with the onboarding module, or get a taste in 5 minutes with the See it work notebook — an offline demo of the finished shapes, before any Python.

  • Short on time? The fast track condenses the whole course into 22 notebooks (~26.5 h).

  • Checking what stuck? Every content module has a short quiz.

How to read a module page

Each module page is that module’s own guide: what you’ll learn, the notebooks in order with time estimates and difficulty, the exercises, and how it connects to the modules on either side. Notebook names link straight to GitHub, where the Colab badge at the top of every notebook opens it in a browser — nothing to install. The three mini-book modules (CI/CD, Django, and Containers & Docker) additionally have their full prose chapters here, listed in the sidebar in reading order.

Browse the course

Modules

Course-wide