#55th of 18 in Learning and cookbooks
ml-for-beginners
12-week, 26-lesson classic machine learning course using Scikit-learn
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- Stars
- 91.5k
- License
- MIT
- Last commit
- Sep 2026
- Language
- Jupyter Notebook
83,785 on 25 Mar 202691,480 on 14 Oct 2026
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Checked on GitHub.
Overview
A Microsoft Cloud Advocates curriculum covering classic machine learning (regression, classification, clustering, NLP) with Scikit-learn, deliberately excluding deep learning. Each lesson has pre- and post-lecture quizzes, a written lesson, a solution, a challenge and an assignment, built around datasets from different world regions. Lessons are in Python, with R Markdown versions for many.
Who it is for: Beginners and teachers learning classic machine learning with Python
Strengths
- Project-based lessons with solutions in /solution folders and quizzes for each lesson
- Many lessons also provided in R as .rmd files
- Translated into 50+ languages via automated GitHub Action
- MIT license; can run in GitHub Codespaces without local Python setup
Weaknesses
- Covers classic ML only; deep learning is in a separate curriculum
- Not about LLMs or generative AI
- Clone is large because of 50+ translations unless sparse checkout is used
- Per-lesson dependencies must be installed manually
What it needs
- no GPU
- Needs Python, Scikit-learn, Jupyter, R (optional)
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