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[](https://GitHub.com/microsoft/AI-For-Beginners/issues/)
[](https://GitHub.com/microsoft/AI-For-Beginners/pulls/)
[](http://makeapullrequest.com)
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[](https://GitHub.com/microsoft/AI-For-Beginners/network/)
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[](https://discord.gg/nTYy5BXMWG)
# 人工智能初学者课程
||
|:---:|
| 人工智能初学者 - _由[@girlie_mac](https://twitter.com/girlie_mac)手绘速记_ |
通过我们的12周、24节课课程探索人工智能（AI）的世界！课程包括实用的课程内容、测验和实验。课程适合初学者，涵盖了TensorFlow和PyTorch等工具，以及AI伦理。
### 🌐 多语言支持
#### 通过GitHub Action支持（自动且始终保持最新）
[阿拉伯语](../ar/README.md) | [孟加拉语](../bn/README.md) | [保加利亚语](../bg/README.md) | [缅甸语 (Myanmar)](../my/README.md) | [中文（简体）](./README.md) | [中文（繁体，香港）](../zh-HK/README.md) | [中文（繁体，澳门）](../zh-MO/README.md) | [中文（繁体，台湾）](../zh-TW/README.md) | [克罗地亚语](../hr/README.md) | [捷克语](../cs/README.md) | [丹麦语](../da/README.md) | [荷兰语](../nl/README.md) | [爱沙尼亚语](../et/README.md) | [芬兰语](../fi/README.md) | [法语](../fr/README.md) | [德语](../de/README.md) | [希腊语](../el/README.md) | [希伯来语](../he/README.md) | [印地语](../hi/README.md) | [匈牙利语](../hu/README.md) | [印尼语](../id/README.md) | [意大利语](../it/README.md) | [日语](../ja/README.md) | [卡纳达语](../kn/README.md) | [高棉语](../km/README.md) | [韩语](../ko/README.md) | [立陶宛语](../lt/README.md) | [马来语](../ms/README.md) | [马拉雅拉姆语](../ml/README.md) | [马拉地语](../mr/README.md) | [尼泊尔语](../ne/README.md) | [尼日利亚皮钦语](../pcm/README.md) | [挪威语](../no/README.md) | [波斯语(Farsi)](../fa/README.md) | [波兰语](../pl/README.md) | [葡萄牙语（巴西）](../pt-BR/README.md) | [葡萄牙语（葡萄牙）](../pt-PT/README.md) | [旁遮普语（Gurmukhi）](../pa/README.md) | [罗马尼亚语](../ro/README.md) | [俄语](../ru/README.md) | [塞尔维亚语（西里尔字母）](../sr/README.md) | [斯洛伐克语](../sk/README.md) | [斯洛文尼亚语](../sl/README.md) | [西班牙语](../es/README.md) | [斯瓦希里语](../sw/README.md) | [瑞典语](../sv/README.md) | [他加禄语（菲律宾语）](../tl/README.md) | [泰米尔语](../ta/README.md) | [泰卢固语](../te/README.md) | [泰语](../th/README.md) | [土耳其语](../tr/README.md) | [乌克兰语](../uk/README.md) | [乌尔都语](../ur/README.md) | [越南语](../vi/README.md)
> **想要本地克隆？**
>
> 本仓库包含50多种语言的翻译版本，显著增加了下载大小。若想不包含翻译内容克隆，请使用稀疏检出：
>
> **Bash / macOS / Linux:**
> ```bash
> 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）：**
> ```cmd
> 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"
> ```
>
> 这样你将获得完整课程内容，同时下载速度更快。
**如果您希望支持其他翻译语言，详情见 [这里](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## 加入社区
[](https://discord.gg/nTYy5BXMWG)
## 你将学到什么
**[课程思维导图](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
在本课程中，你将学习：
* 不同的人工智能方法，包括“老派”的符号方法以及知识表示与推理([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
* 现代AI核心的神经网络和深度学习。我们会通过代码示例讲解这些重要主题的概念，使用两种最流行的框架——[TensorFlow](http://Tensorflow.org)和[PyTorch](http://pytorch.org)。
* 用于处理图像和文本的神经架构。我们会介绍近期的模型，但可能稍显不足于最新技术。
* 较少使用的AI方法，如遗传算法和多智能体系统。
本课程不涉及内容：
> [在我们的Microsoft Learn合集里找到本课程所有额外资源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **AI在商业中的应用案例**。建议学习微软Learn上的[面向商务用户的AI入门](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)课程或由[INSEAD](https://www.insead.edu/)协作开发的[人工智能商学院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* 经典机器学习，在我们的[初学者机器学习课程](http://github.com/Microsoft/ML-for-Beginners)中有详细描述。
* 基于[认知服务](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)的实际AI应用。建议先从微软Learn上的[计算机视觉](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然语言处理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、[Azure OpenAI 服务生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)等模块开始学习。
* 特定的机器学习云框架，如[Azure 机器学习](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、或[Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。推荐使用[使用 Azure 机器学习构建和运行机器学习解决方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)和[在 Azure Databricks 上构建和运行机器学习解决方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)学习路径。
* 会话式AI和聊天机器人。有专门的[创建会话式AI解决方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)学习路径，也可以参考[此博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)了解详细内容。
* 深度学习背后的深度数学。推荐阅读Ian Goodfellow、Yoshua Bengio和Aaron Courville合著的[Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，在线版本请访问[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
对于轻松入门云端的_Ai_相关话题，建议学习[在Azure上入门人工智能](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)学习路径。
# 课程内容
| | 课程链接 | PyTorch/Keras/TensorFlow | 实验 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [课程环境设置](./lessons/0-course-setup/setup.md) | [搭建开发环境](./lessons/0-course-setup/how-to-run.md) | |
| I | [人工智能简介](./lessons/1-Intro/README.md) | | |
| 01 | [人工智能介绍与历史](./lessons/1-Intro/README.md) | - | - |
| II | **符号AI** |
| 02 | [知识表示与专家系统](./lessons/2-Symbolic/README.md) | [专家系统](./lessons/2-Symbolic/Animals.ipynb) / [本体论](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念图谱](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [神经网络简介](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [笔记本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [实验](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多层感知器及创建我们的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [笔记本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [实验](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架简介（PyTorch/TensorFlow）及过拟合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [计算机视觉](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [在 Microsoft Azure 上探索计算机视觉](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [计算机视觉简介。OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [笔记本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [实验](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷积神经网络](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架构](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [实验](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [预训练网络与迁移学习](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [训练技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自编码器与变分自编码器 (VAE)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成对抗网络与艺术风格迁移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [目标检测](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [实验](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [语义分割。U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [自然语言处理](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [在 Microsoft Azure 上探索自然语言处理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示。词袋模型/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [语义词嵌入。Word2Vec和GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [语言建模。自定义嵌入训练](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [实验](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循环神经网络](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成循环网络](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [实验](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [变换器。BERT。](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名实体识别](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [实验](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型语言模型，提示编程与少样本任务](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **其他AI技术** || |
| 21 | [遗传算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [笔记本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深度强化学习](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [实验](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [多智能体系统](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | 人工智能伦理 | | |
| 24 | [人工智能伦理与负责任的AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 负责任的AI原则](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | 附加内容 | | |
| 25 | [多模态网络，CLIP 与 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [笔记本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每节课包含
* 预习材料
* 可执行的 Jupyter 笔记本，通常针对特定框架（**PyTorch** 或 **TensorFlow**）。可执行笔记本还包含大量理论内容，因此要理解主题，你需要至少通读其中一个版本的笔记本（PyTorch 或 TensorFlow）。
* 一些主题配有实验，让你有机会将所学内容应用到具体问题中。
* 部分章节含有指向涵盖相关主题的[**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)模块的链接。
## 入门指南
### 🎯 AI 新手？从这里开始！
如果你完全是 AI 新手，想要快速获得动手示例，请查看我们的[初学者示例](./examples/README.md)！内容包括：
- 🌟 **Hello AI World** - 你的第一个 AI 程序（模式识别）
- 🧠 简单神经网络 - 从零构建神经网络
- 🖼️ 图像分类器 - 带详细注释的图像分类
- 💬 文本情感分析 - 分析正面/负面文本
这些示例设计帮助你在深入完整课程前理解 AI 概念。
### 📚 完整课程设置
- 我们制作了一个[安装课程](./lessons/0-course-setup/setup.md)，帮助你搭建开发环境。
- 对于教师，我们也制作了一个[课程设置教程](./lessons/0-course-setup/for-teachers.md)！
- 如何在 VSCode 或 Codespace 中[运行代码](./lessons/0-course-setup/how-to-run.md)
请遵循以下步骤：
仓库 Fork：点击本页右上角的“Fork”按钮。
仓库克隆：`git clone https://github.com/microsoft/AI-For-Beginners.git`
别忘了给该仓库点星（🌟），方便以后找到它。
## 认识其他学习者
加入我们的[官方 AI Discord 服务器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，结识和交流学习本课程的其他学习者，并获得支持。
如果在构建过程中有产品反馈或问题，请访问我们的[Azure AI Foundry 开发者论坛](https://aka.ms/foundry/forum)
## 测验
> 关于测验的说明：所有测验都包含在 etc\quiz-app 目录下的 Quiz-app 文件夹中，或可[在此在线访问](https://ff-quizzes.netlify.app/)。测验从课程中链接，测验应用程序可以本地运行或部署到 Azure；请按 `quiz-app` 文件夹中的说明操作。目前测验正在逐步本地化。
## 需要帮助
你有建议或者发现拼写或代码错误吗？请提交 issue 或创建 pull request。
## 特别感谢
* **✍️ 主要作者：** [Dmitry Soshnikov](http://soshnikov.com)，博士
* **🔥 编辑：** [Jen Looper](https://twitter.com/jenlooper)，博士
* **🎨 速写插画师：** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ 测验创建者：** [Lateefah Bello](https://github.com/CinnamonXI)，[MLSA](https://studentambassadors.microsoft.com/)
* **🙏 核心贡献者：** [Evgenii Pishchik](https://github.com/Pe4enIks)
## 其他课程体系
我们的团队还制作了其他课程！查看：
### LangChain
[](https://aka.ms/langchain4j-for-beginners)
[](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin)
[](https://github.com/microsoft/langchain-for-beginners?WT.mc_id=m365-94501-dwahlin)
---
### Azure / Edge / MCP / Agents
[](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst)
---
### 生成式 AI 系列
[](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst)
[-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst)
[-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst)
[-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst)
---
### 核心学习
[](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung)
[](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst)
---
### Copilot 系列
[](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst)
## 获取帮助
如果遇到瓶颈或有任何关于构建 AI 应用的问题，欢迎加入 MCP 学习者和资深开发者的讨论社区。这里是一个友好支持的社区，欢迎提问并自由分享知识。
[](https://discord.gg/nTYy5BXMWG)
如果在构建过程中有产品反馈或遇到问题，请访问：
[](https://aka.ms/foundry/forum)
---
**免责声明**：
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