What’s new

This course is an early release. Like an early-release book, it is complete enough to learn from, but it is still being finished: pages may change, and some parts are not available yet. Version numbers below 1.0 mark the early release. Version 1.0 follows when the Kaggle competitions are open and the course has been checked from start to finish.

Found a mistake or something unclear? Use “Report an issue” on any page, or open an issue on GitHub.

Coming next

• The Kaggle competitions for stability and energy levels (early 2027).

v0.2.0 · 1 November 2026

• New: How to use this course, with paths for different learners, an 8-week plan, what you need and where to get help.
• New: Set up your computer, the step-by-step setup guide (also used to be in the repository’s README only).
• The course Discussions are open: ask questions, help others, share what you built.

v0.1.1 · 1 November 2026

• The course has its permanent address on the website of Applied Data Science & AI: https://ai.buas.nl/open-courses/introduction-to-ml/. The old address on github.io forwards here.

v0.1.0 · 1 November 2026

First public early release, adapted from the 2026/27 edition of the course at Breda University of Applied Sciences.

• Self-study: six themes with eleven notebooks and twelve reading and activity pages.
• DataLab: Iterations 1, 2 and 3+, with the course’s own edition of the data, including a lab database for Iteration 3+.
• Setup: one Python environment (Python 3.13, managed with uv) with every package the course uses.
• License: content CC BY 4.0, code MIT, so you can reuse the course in your own teaching.