开源教程强烈推荐：《AI For Beginners》—— 微软出品：12 周 24 课从零学 AI，含多智能体系统、强化学习、AI 伦理全覆盖

想系统学 AI 但不知道从哪开始？微软把一套完整的 AI 大学课程开源了：12 周、24 节课，用 Jupyter Notebook 配合实操实验，从神经网络基础一路到多智能体系统。

该项目不只是理论，每课都有测验、Lab 实验和项目，TensorFlow + PyTorch 双框架并行，还有专门的 AI 伦理与负责任 AI 模块。

核心特性：

1. 12 周系统课程：从 AI 基础到深度学习、NLP、强化学习、多智能体系统
2. 每课含测验 + Lab：动手实验配合理论，有实际可运行代码
3. TensorFlow + PyTorch 双轨：框架不锁定，学完自选
4. 多智能体系统专章：遗传算法、强化学习、Multi-Agent 系统完整讲解
5. AI 伦理模块：内置负责任 AI 思考框架，不回避现实问题
6. 多语言社区版本：全球开发者社区维护多语言翻译

特别适合正在入门 AI、或已经在用 AI 工具但想补全基础理论体系的工程师和开发者。目前 50.7k+ stars，是微软 GitHub 上最受欢迎的 AI 教育资源，多年持续更新维护。

与现有 AI 教程资源的互补差异：大多数 AI 课程要么太浅（ChatGPT 提示工程入门）、要么太深（论文级数学推导）；AI-For-Beginners 定位在工程实践层，能运行的代码、可解释的概念、真实可测的知识点。对已经在用 Claude Code 等 AI 工具的开发者，这是补全「为什么 AI 这样工作」底层逻辑的最好起点之一。

https://github.com/microsoft/AI-For-Beginners…

#AI教程 #LLMFromScratch #AIEngineering #AI编程 #微软开源

microsoft/AI-For-Beginners

Source: https://github.com/microsoft/AI-For-Beginners

Artificial Intelligence for Beginners - A Curriculum

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

🌐 Multi-Language Support

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

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

Prefer to Clone Locally?

This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:

Bash / macOS / Linux:

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'

CMD (Windows):

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"

This gives you everything you need to complete the course with a much faster download.

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

Join the Community

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

• Business cases of using AI in Business. Consider taking Introduction to AI for business users learning path on Microsoft Learn, or AI Business School, developed in cooperation with INSEAD.
• Classic Machine Learning, which is well described in our Machine Learning for Beginners Curriculum.
• Practical AI applications built using Cognitive Services. For this, we recommend that you start with modules Microsoft Learn 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 detail.
• Deep Mathematics behind deep learning. For this, we would recommend Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at https://www.deeplearningbook.org/.

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

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 Codespace

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 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

• ✍️ 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 produces other curricula! Check out:

LangChain

Azure / Edge / MCP / Agents

Generative AI Series

Core Learning

Copilot Series

Getting Help

If you get stuck or have any questions about building AI apps. Join fellow learners and experienced developers in discussions about MCP. It’s a supportive community where questions are welcome and knowledge is shared freely.

If you have product feedback or errors while building visit: