Guide · Open source
How to use AI-For-Beginners: clone the course and start lessons
Updated · written with AI from the project's own documentation and checked against our catalogue data
AI-For-Beginners is a free, open-source curriculum from Microsoft that teaches artificial intelligence over 12 weeks and 24 lessons. It is hosted on GitHub, so you can read the lessons, run the code and contribute fixes. This guide shows you how to download the course with Git, what the material covers, and how to decide whether it fits your goals.
AI-For-Beginnersmicrosoft/AI-For-Beginners · ★ 70.5k · MIT Install options & downloads Quick start
- 1Check that Git is installed. The only prerequisite listed is Git. Install it first if your system does not have it.
- 2Clone the repository with sparse checkout. Run the git clone command with --filter=blob:none --sparse to skip the large translation folders.
- 3Enter the folder and set the sparse rules. Move into AI-For-Beginners and run git sparse-checkout set with the exclusions for translations and translated_images.
- 4Open the first lesson. Browse the lesson folders and start with the first of the 24 lessons.
- 5Work through quizzes and labs. Complete each lesson's quiz and lab before moving on, following the 12-week structure.
What the AI-For-Beginners course covers
The curriculum is beginner-friendly and includes practical lessons, quizzes, and labs. It also covers ethics in AI alongside the technical topics.
The README lists these areas: symbolic AI (GOFAI) with knowledge representation and reasoning, neural networks and deep learning using TensorFlow and PyTorch, neural architectures for images and text, and less popular approaches such as genetic algorithms and multi-agent systems.
- Symbolic AI with knowledge representation and reasoning
- Neural networks and deep learning in TensorFlow and PyTorch
- Neural architectures for images and text
- Genetic algorithms and multi-agent systems
What the course does not cover
The README says the course does not cover business cases for AI, classic machine learning, or practical applications built with Cognitive Services. For business material it points to Microsoft Learn paths, and for classic machine learning it points to the separate Machine Learning for Beginners curriculum.
It also says recent models are included but may be somewhat lacking in state-of-the-art detail, so it is not the place to learn the newest models.
Download the course with Git
The README recommends a sparse checkout, which skips the many translation folders and makes the download much smaller. You need Git installed. Run the first command to clone the repository without its blobs, then enter the folder and set the sparse checkout.
The README also provides a CMD version for Windows, which uses double quotes instead of single quotes.
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'Work through the lessons
The course runs over 12 weeks with 24 lessons. Each lesson includes practical material, a quiz, and labs. Open the lesson folders in the cloned repository and work through them in order, since the concepts build on each other.
The README also links a mindmap of the course and a Microsoft Learn collection with additional resources. Use these as a map when you want to see how the topics connect.
- Follow the lessons in order over the 12-week schedule
- Complete the quiz and lab for each lesson
- Use the mindmap and Microsoft Learn collection for extra context
Get help and contribute
The README invites contributions, including fixing typos, improving documentation, or adding examples. The contributing guide is named CONTRIBUTING.md in the repository. A community Discord is linked from the README.
- Read CONTRIBUTING.md before opening a pull request
- Join the Discord linked in the README to ask questions
What people use it for
- Learning the basics of neural networks with TensorFlow or PyTorch code
- Building a structured self-study plan for a first AI course
- Exploring symbolic AI, genetic algorithms, and multi-agent systems
- Reading the ethics material alongside technical lessons
- Contributing a typo fix or example to an open curriculum
Frequently asked questions
Is AI-For-Beginners free?
Yes. The README describes it as a free curriculum from Microsoft, and the repository is published under the MIT licence. You can clone it, read it and reuse it under those terms.
What do I need to use AI-For-Beginners?
The README lists Git as the prerequisite for cloning the repository. The course content is in Jupyter Notebook and uses TensorFlow and PyTorch for its code examples.
Why use sparse checkout when cloning?
The repository includes more than 50 language translations, which increases the download size. The sparse checkout commands skip the translations and translated_images folders for a much faster download.
Does AI-For-Beginners cover classic machine learning?
No. The README says classic machine learning is covered in the separate Machine Learning for Beginners curriculum from Microsoft.
Is AI-For-Beginners good for the latest AI models?
Not especially. The README says recent models are covered but may be somewhat lacking in state-of-the-art detail.
What are alternatives to AI-For-Beginners?
Comparable projects named in this directory are Machine Learning for Beginners from Microsoft, fast.ai course materials, and Dive into Deep Learning.
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Our verdict
AI-For-Beginners suits beginners who want a free, structured, self-paced introduction to AI, and developers who want to learn neural networks in TensorFlow or PyTorch. If you want business strategy, classic machine learning, or the newest state-of-the-art models, the README points you to other resources instead.
Install options & downloads