Illustration of what AI-For-Beginners does: A free 12-week, 24-lesson course on AI with notebooks, quizzes and labs

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AI-For-Beginners

A free 12-week, 24-lesson course on AI with notebooks, quizzes and labs

This is a self-paced course, not a software library. It runs 12 weeks across 24 lessons. Each lesson has written material, and many have a notebook and a lab to practise on.

It starts with the older symbolic approach, where knowledge is written down as rules and ontologies. It then moves to neural networks and deep learning, with code in TensorFlow and PyTorch. Later lessons cover architectures for images and text, plus less common topics such as genetic algorithms and multi-agent systems.

The README is clear about what it leaves out. Classic machine learning is covered in Microsoft's separate Machine Learning for Beginners course. Business use of AI, Azure cloud services, chatbots and the deep maths are pointed to other resources. It also says its coverage of recent models may lag the state of the art.

What it does

  • Structured 12-week path

    24 lessons come with quizzes and labs alongside the reading.

  • Notebooks in two frameworks

    Lessons include Jupyter notebooks in PyTorch, Keras and TensorFlow, so you can compare them.

  • Symbolic AI to neural networks

    Covers expert systems and ontologies, then perceptrons, multi-layer networks and building your own small framework before using standard ones.

  • Computer vision track

    Starts with OpenCV and moves on to convolutional neural networks and their architectures.

  • 50+ translations

    The README lists more than 50 languages and explains a sparse checkout that skips translations to shrink the download.

What you could build

  • Follow a full beginner course on AI over about three months.
  • Run the Jupyter notebooks to see how a perceptron and a neural network work in code.
  • Compare the same neural network written in PyTorch, Keras and TensorFlow.
  • Teach an introductory AI class using the lessons, labs and quizzes.
  • Learn the basics of computer vision with OpenCV and convolutional networks.

Get started

Clone the repository, using the sparse checkout if you want to skip the translations, then open the course setup lesson to prepare your environment. The README also links a Binder badge for running notebooks online.

git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

Commands are copied from the project's README. Read it on GitHub for the full setup.

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