AI-For-Beginners README

The project's README from github.com/microsoft/AI-For-Beginners. As one markdown file: README.md.

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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

🌐 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

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🤝 Contributing

We welcome contributions from the community! Whether you're fixing typos, improving documentation, or adding new examples, your help makes this curriculum better for everyone. Check out our CONTRIBUTING.md guide to get started.

What you will learn

Mindmap of the Course

In this curriculum, you will learn:

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 Link PyTorch/Keras/TensorFlow Lab
0 Course Setup Setup Your Development Environment
I Introduction to AI
01 Introduction and History of AI - -
II Symbolic AI
02 Knowledge Representation and Expert Systems Expert Systems / Ontology /Concept Graph
III Introduction to Neural Networks
03 Perceptron Notebook Lab
04 Multi-Layered Perceptron and Creating our own Framework Notebook Lab
05 Intro to Frameworks (PyTorch/TensorFlow) and Overfitting PyTorch / Keras / TensorFlow Lab
IV Computer Vision PyTorch / TensorFlow Explore Computer Vision on Microsoft Azure
06 Intro to Computer Vision. OpenCV Notebook Lab
07 Convolutional Neural Networks & CNN Architectures PyTorch /TensorFlow Lab
08 Pre-trained Networks and Transfer Learning and Training Tricks PyTorch / TensorFlow Lab
09 Autoencoders and VAEs PyTorch / TensorFlow
10 Generative Adversarial Networks & Artistic Style Transfer PyTorch / TensorFlow
11 Object Detection TensorFlow Lab
12 Semantic Segmentation. U-Net PyTorch / TensorFlow
V Natural Language Processing PyTorch /TensorFlow Explore Natural Language Processing on Microsoft Azure
13 Text Representation. Bow/TF-IDF PyTorch / TensorFlow
14 Semantic word embeddings. Word2Vec and GloVe PyTorch / TensorFlow
15 Language Modeling. Training your own embeddings PyTorch / TensorFlow Lab
16 Recurrent Neural Networks PyTorch / TensorFlow
17 Generative Recurrent Networks PyTorch / TensorFlow Lab
18 Transformers. BERT. PyTorch /TensorFlow
19 Named Entity Recognition TensorFlow Lab
20 Large Language Models, Prompt Programming and Few-Shot Tasks PyTorch
VI Other AI Techniques
21 Genetic Algorithms Notebook
22 Deep Reinforcement Learning PyTorch /TensorFlow Lab
23 Multi-Agent Systems
VII AI Ethics
24 AI Ethics and Responsible AI

AI-For-Beginners (microsoft/AI-For-Beginners)

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这是什么?这是微软推出的一门免费课程,共 12 周、24 节课,通过实践课程、测验和实验讲解人工智能基础知识。
这是门课程还是参考书?这是一门结构化课程,由按周划分的 Jupyter Notebook 课程组成,而不是一本书或速查手册。
我该如何开始学习这些课程?先克隆仓库,从 'Course Setup' 课程开始配置开发环境,然后按编号顺序(01 到 24)依次学习各节课。
我需要安装 PyTorch 或 TensorFlow 吗?需要。大多数课程同时提供 PyTorch 和 TensorFlow/Keras 版本的 notebook,所以你需要至少配置其中一个框架才能运行实验。
完整仓库下载很大吗?是的,因为它包含 50 多种完整的语言翻译。如果只想下载英文内容,可以使用 sparse checkout 只克隆英文部分、跳过翻译,这样下载会快得多。
我需要有机器学习经验才能开始吗?不需要,这门课程专门为刚接触人工智能的初学者设计。
这门课程涵盖哪些主题?内容包括符号式 AI、神经网络、计算机视觉(CNN、GAN、目标检测)、自然语言处理(词嵌入、RNN、Transformer、BERT、LLM)、遗传算法、多智能体系统、深度强化学习和 AI 伦理。
这门课程有意跳过了哪些内容?它不涵盖经典机器学习(另有独立的 'Machine Learning for Beginners' 课程)、深度学习背后的深入数学原理、Azure Machine Learning 等云端专用机器学习框架,也不深入讲解对话式 AI 和聊天机器人。
有英语以外的其他语言版本吗?有。课程通过 GitHub Action 自动翻译成 50 多种语言,包括阿拉伯语、中文、法语、德语、印地语、日语、俄语和西班牙语。
有测验来检验我的理解吗?有。课程中每个主题的讲解和实验之外,都配有测验。
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microsoft
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Updated
CommitSep 04
Age
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Commits · 90 Days