README

🌐 Multi-Language Support

 Translations maintained with Co-op Translator


Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | Chinese (Traditional, Taiwan) | Croatian | Czech | Danish | Dutch | Estonian | Finnish | French | German | Greek | Hebrew | Hindi | Hungarian | Indonesian | Italian | Japanese | Kannada | Khmer | Korean | Lithuanian | Malay | Malayalam | Marathi | Nepali | Nigerian Pidgin | Norwegian | Persian (Farsi) | Polish | Portuguese (Brazil) | Portuguese (Portugal) | Punjabi (Gurmukhi) | Romanian | Russian | Serbian (Cyrillic) | Slovak | Slovenian | Spanish | Swahili | Swedish | Tagalog (Filipino) | Tamil | Telugu | Thai | Turkish | Ukrainian | Urdu | Vietnamese

 Prefer to Clone Locally?

 This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:

 Bash / macOS / Linux:
 bash
 git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git
 cd ML-For-Beginners
 git sparse-checkout set --no-cone '/' '!translations' '!translated_images'
 

 CMD (Windows):
 cmd
 git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git
 cd ML-For-Beginners
 git sparse-checkout set --no-cone "/" "!translations" "!translated_images"
 

 This gives you everything you need to complete the course with a much faster download.


 Join Our Community



We have a Discord learn with AI series ongoing, learn more and join us at Learn with AI Series from 18 - 30 September, 2025. You will get tips and tricks of using GitHub Copilot for Data Science.

!Learn with AI series

 Machine Learning for Beginners - A Curriculum

 🌍 Travel around the world as we explore Machine Learning by means of world cultures 🌍

Cloud Advocates at Microsoft are pleased to offer a 12-week, 26-lesson curriculum all about Machine Learning. In this curriculum, you will learn about what is sometimes called classic machine learning, using primarily Scikit-learn as a library and avoiding deep learning, which is covered in our AI for Beginners' curriculum. Pair these lessons with our 'Data Science for Beginners' curriculum, as well!

Travel with us around the world as we apply these classic techniques to data from many areas of the world. Each lesson includes pre- and post-lesson quizzes, written instructions to complete the lesson, a solution, an assignment, and more. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.

✍️ Hearty thanks to our authors Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu and Amy Boyd

🎨 Thanks as well to our illustrators Tomomi Imura, Dasani Madipalli, and Jen Looper

🙏 Special thanks 🙏 to our Microsoft Student Ambassador authors, reviewers, and content contributors, notably R

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