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README.md
Artificial Intelligence for Beginners - A Curriculum
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| AI For Beginners - Sketchnote by @girlie_mac |
Dive into the fascinating world of Artificial Intelligence (AI) with our 12-week, 24-lesson curriculum! It includes hands-on lessons, quizzes, and labs. This beginner-friendly curriculum covers tools like TensorFlow and PyTorch, as well as discussions on AI ethics.
🌐 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'd like additional translations, supported languages are listed here
Join the Community
What you will learn
In this curriculum, you will explore:
- Various approaches to Artificial Intelligence, including the "classic" symbolic approach with Knowledge Representation and reasoning (GOFAI).
- Neural Networks and Deep Learning, which are central to modern AI. We'll explain these concepts using code in two popular frameworks - TensorFlow and PyTorch.
- Neural Architectures for processing images and text. While we will cover recent models, we may not delve into the latest advancements.
- Less common AI techniques, such as Genetic Algorithms and Multi-Agent Systems.
What this curriculum does not cover:
Find all additional resources for this course in our Microsoft Learn collection
- Business applications of AI in Business. For this, consider the Introduction to AI for business users learning path on Microsoft Learn, or AI Business School, developed in collaboration with INSEAD.
- Classic Machine Learning, which is thoroughly covered in our Machine Learning for Beginners Curriculum.
- Practical AI applications using Cognitive Services. For this, we recommend starting with Microsoft Learn modules for vision, natural language processing, Generative AI with Azure OpenAI Service, and others.
- Specific ML Cloud Frameworks, such as Azure Machine Learning, Microsoft Fabric, or Azure Databricks. Consider using Build and operate machine learning solutions with Azure Machine Learning and Build and Operate Machine Learning Solutions with Azure Databricks learning paths.
- Conversational AI and Chat Bots. There is a separate Create conversational AI solutions learning path, and you can also refer to this blog post for more details.
- Advanced Mathematics behind deep learning. For this, we recommend Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, which is also available online at https://www.deeplearningbook.org/.
For a beginner-friendly introduction to AI in the Cloud, consider taking the Get started with artificial intelligence on Azure Learning Path.
Content
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
🎯 New to AI? Start Here!
If you're completely new to AI and want quick, hands-on examples, check out our Beginner-Friendly Examples! These include:
- 🌟 Hello AI World - Your first AI program (pattern recognition)
- 🧠 Simple Neural Network - Build a neural network from scratch
- 🖼️ Image Classifier - Classify images with detailed comments
- 💬 Text Sentiment - Analyze positive/negative text
These examples are designed to help you understand AI concepts before diving into the full curriculum.
📚 Full Curriculum Setup
- We have created a setup lesson to help you with setting up your development environment. - For Educators, we have created a curricula setup lesson for you too!
- How to Run the code in a VSCode or a Codepace
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 (🌟) this repo to make it easier to find later.
Connect with Other Learners
Join our official AI Discord server to network with other learners taking this course and get support.
If you have product feedback or questions while building, visit our Azure AI Foundry Developer Forum.
Quizzes
A note about quizzes: All quizzes are located in the Quiz-app folder under etc\quiz-app, or Online Here. They are linked within the lessons. The quiz app can be run locally or deployed to Azure; follow the instructions in the
quiz-appfolder. Localization is being added gradually.
Help Wanted
Have suggestions or found spelling or code errors? Raise an issue or create a pull request.
Special Thanks
- ✍️ Primary Author: Dmitry Soshnikov, PhD
- 🔥 Editor: Jen Looper, PhD
- 🎨 Sketchnote Illustrator: Tomomi Imura
- ✅ Quiz Creator: Lateefah Bello, MLSA
- 🙏 Core Contributors: Evgenii Pishchik
Other Curricula
Our team creates other curricula! Check out:
- Generative AI for Beginners
- Generative AI for Beginners .NET
- Generative AI with JavaScript
- Generative AI with Java
- AI for Beginners
- Data Science for Beginners
- ML for Beginners
- Cybersecurity for Beginners
- Web Dev for Beginners
- IoT for Beginners
- XR Development for Beginners
- Mastering GitHub Copilot for Agentic Use
- Mastering GitHub Copilot for C#/.NET Developers
- Choose Your Own Copilot Adventure
Getting Help
If you're stuck or have questions about building AI apps, join:
If you have product feedback or encounter errors while building, visit:
Disclaimer:
This document has been translated using the AI translation service Co-op Translator. While we aim for accuracy, please note that automated translations may contain errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is recommended. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.