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    microsoft/AI-For-Beginners

    12 Weeks, 24 Lessons, AI for All!

    ai
    deep-learning
    computer-vision
    machine-learning
    nlp
    artificial-intelligence
    cnn
    gan
    microsoft-for-beginners
    rnn
    Jupyter Notebook
    MIT
    42.8K stars
    8.3K forks
    42.8K watching
    Updated 2/27/2026
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    About AI-For-Beginners

    GitHub license GitHub contributors GitHub issues GitHub pull-requests PRs Welcome

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    Artificial Intelligence for Beginners - A Curriculum

    Sketchnote by @girlie_mac https://twitter.com/girlie_mac
    AI For Beginners - Sketchnote by @girlie_mac

    Explore the world of Artificial Intelligence (AI) with our 12-week, 24-lesson curriculum! It includes practical lessons, quizzes, and labs. The curriculum is beginner-friendly and covers tools like TensorFlow and PyTorch, as well as ethics in AI

    ๐ŸŒ Multi-Language Support

    Supported via GitHub Action (Automated & Always Up-to-Date)

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

    If you wish to have additional translations languages supported are listed here

    Join the Community

    Azure AI Discord

    What you will learn

    Mindmap of the Course

    In this curriculum, you will learn:

    • Different approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (GOFAI).
    • Neural Networks and Deep Learning, which are at the core of modern AI. We will illustrate the concepts behind these important topics using code in two of the most popular frameworks - TensorFlow and PyTorch.
    • Neural Architectures for working with images and text. We will cover recent models but may be a bit lacking in the state-of-the-art.
    • Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.

    What we will not cover in this curriculum:

    Find all additional resources for this course in our Microsoft Learn collection

    For a gentle introduction to AI in the Cloud topics you may consider taking the Get started with artificial intelligence on Azure Learning Path.

    Content

    Lesson LinkPyTorch/Keras/TensorFlowLab
    0Course SetupSetup Your Development Environment
    IIntroduction to AI
    01Introduction and History of AI--
    IISymbolic AI
    02Knowledge Representation and Expert SystemsExpert Systems / Ontology /Concept Graph
    IIIIntroduction to Neural Networks
    03PerceptronNotebookLab
    04Multi-Layered Perceptron and Creating our own FrameworkNotebookLab
    05Intro to Frameworks (PyTorch/TensorFlow) and OverfittingPyTorch / Keras / TensorFlowLab
    IVComputer VisionPyTorch / TensorFlowExplore Computer Vision on Microsoft Azure
    06Intro to Computer Vision. OpenCVNotebookLab
    07Convolutional Neural Networks & CNN ArchitecturesPyTorch /TensorFlowLab
    08Pre-trained Networks and Transfer Learning and Training TricksPyTorch / TensorFlowLab
    09Autoencoders and VAEsPyTorch / TensorFlow
    10Generative Adversarial Networks & Artistic Style TransferPyTorch / TensorFlow
    11Object DetectionTensorFlowLab
    12Semantic Segmentation. U-NetPyTorch / TensorFlow
    VNatural Language ProcessingPyTorch /TensorFlowExplore Natural Language Processing on Microsoft Azure
    13Text Representation. Bow/TF-IDFPyTorch / TensorFlow
    14Semantic word embeddings. Word2Vec and GloVePyTorch / TensorFlow
    15Language Modeling. Training your own embeddingsPyTorch / TensorFlowLab
    16Recurrent Neural NetworksPyTorch / TensorFlow
    17Generative Recurrent NetworksPyTorch / TensorFlowLab
    18Transformers. BERT.PyTorch /TensorFlow
    19Named Entity RecognitionTensorFlowLab
    20Large Language Models, Prompt Programming and Few-Shot TasksPyTorch
    VIOther AI Techniques
    21Genetic AlgorithmsNotebook
    22Deep Reinforcement LearningPyTorch /TensorFlowLab
    23Multi-Agent Systems
    VIIAI Ethics
    24AI Ethics and Responsible AIMicrosoft Learn: Responsible AI Principles
    IXExtras
    25Multi-Modal Networks, CLIP and VQGANNotebook

    Each lesson contains

    • Pre-reading material
    • Executable Jupyter Notebooks, which are often specific to the framework (PyTorch or TensorFlow). The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebook (either PyTorch or TensorFlow).
    • Labs available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem.
    • Some sections contain links to MS Learn modules that cover related topics.

    Getting Started

    Follow these steps:

    Fork the Repository: Click on the "Fork" button at the top-right corner of this page.

    Clone the Repository: git clone https://github.com/microsoft/AI-For-Beginners.git

    Don't forget to star (๐ŸŒŸ) this repo to find it easier later.

    Meet other Learners

    Join our official AI Discord server to meet and network with other learners taking this course and get support.

    If you have product feedback or questions whilst building visit our Azure AI Foundry Developer Forum

    Quizzes

    A note about quizzes: All quizzes are contained in the Quiz-app folder in etc\quiz-app, or Online Here They are linked from within the lessons the quiz app can be run locally or deployed to Azure; follow the instruction in the quiz-app folder. They are gradually being localized.

    Help Wanted

    Do you have suggestions or found spelling or code errors? Raise an issue or create a pull request.

    Special Thanks

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