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Data Science for Beginners - A Curriculum
Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.
This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:
Bash / macOS / Linux:
git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git
cd Data-Science-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
CMD (Windows):
git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git
cd Data-Science-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.
If you wish to have additional translations languages supported are listed here
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.
Are you a student?
Get started with the following resources:
Student Hub page In this page, you will find beginner resources, Student packs and even ways to get a free cert voucher. This is one page you want to bookmark and check from time to time as we switch out content at least monthly.
For Teachers - Teaching guidance and classroom resources
👨🎓 For Students
Complete Beginners: New to data science? Start with our beginner-friendly examples! These simple, well-commented examples will help you understand the basics before diving into the full curriculum.
Students: to use this curriculum on your own, fork the entire repo and complete the exercises on your own, starting with a pre-lecture quiz. Then read the lecture and complete the rest of the activities. Try to create the projects by comprehending the lessons rather than copying the solution code; however, that code is available in the /solutions folders in each project-oriented lesson. Another idea would be to form a study group with friends and go through the content together. For further study, we recommend Microsoft Learn.
🎥 Click the image above for a video about the project the folks who created it!
Pedagogy
We have chosen two pedagogical tenets while building this curriculum: ensuring that it is project-based and that it includes frequent quizzes. By the end of this series, students will have learned basic principles of data science, including ethical concepts, data preparation, different ways of working with data, data visualization, data analysis, real-world use cases of data science, and more.
In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 10 week cycle.
