Microsoft's AI-For-Beginners Hits 66K Stars Teaching Neural Networks From Scratch
Microsoft's free 12-week curriculum walks you through neural networks, computer vision, NLP, and transformers using PyTorch and TensorFlow notebooks.
PRO- Microsoft's AI-For-Beginners is a free 12-week, 24-lesson curriculum on GitHub
- Covers symbolic AI, neural networks, CNNs, GANs, transformers, RL, and ethics
- Every lesson ships as runnable Jupyter notebooks in both PyTorch and TensorFlow
- Includes pre-reading, quizzes, hands-on labs, and links to Microsoft Learn modules
- Translated into 50+ languages, MIT licensed, and runnable in Codespaces or Binder
- Part of a wider beginner series including Generative AI and AI Agents tracks
If you have been meaning to actually understand what happens inside a neural network instead of just calling an API, Microsoft's AI-For-Beginners curriculum is worth a serious look. The repo has crossed 66,000 stars on GitHub and packages a full university-style AI course into runnable Jupyter notebooks, with quizzes, labs, and translations into more than 50 languages.
What you actually get
The curriculum spans 12 weeks and 24 lessons, stays beginner-friendly, and covers TensorFlow, PyTorch, and ethics in AI. The structure is broader than most modern courses, which tend to jump straight to transformers. Microsoft goes back to first principles and then works forward.
The lessons are grouped into sections that build on each other:
- Symbolic AI including knowledge representation, expert systems, and ontologies
- Neural network fundamentals, up to building your own mini-framework as a multi-layered perceptron exercise
- Computer vision: OpenCV, CNNs, transfer learning, autoencoders, GANs, object detection, and U-Net segmentation
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