[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-microsoft--AI-For-Beginners":3,"tool-microsoft--AI-For-Beginners":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",144730,2,"2026-04-07T23:26:32",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",107888,"2026-04-06T11:32:50",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":10,"last_commit_at":59,"category_tags":60,"status":17},4487,"LLMs-from-scratch","rasbt\u002FLLMs-from-scratch","LLMs-from-scratch 是一个基于 PyTorch 的开源教育项目，旨在引导用户从零开始一步步构建一个类似 ChatGPT 的大型语言模型（LLM）。它不仅是同名技术著作的官方代码库，更提供了一套完整的实践方案，涵盖模型开发、预训练及微调的全过程。\n\n该项目主要解决了大模型领域“黑盒化”的学习痛点。许多开发者虽能调用现成模型，却难以深入理解其内部架构与训练机制。通过亲手编写每一行核心代码，用户能够透彻掌握 Transformer 架构、注意力机制等关键原理，从而真正理解大模型是如何“思考”的。此外，项目还包含了加载大型预训练权重进行微调的代码，帮助用户将理论知识延伸至实际应用。\n\nLLMs-from-scratch 特别适合希望深入底层原理的 AI 开发者、研究人员以及计算机专业的学生。对于不满足于仅使用 API，而是渴望探究模型构建细节的技术人员而言，这是极佳的学习资源。其独特的技术亮点在于“循序渐进”的教学设计：将复杂的系统工程拆解为清晰的步骤，配合详细的图表与示例，让构建一个虽小但功能完备的大模型变得触手可及。无论你是想夯实理论基础，还是为未来研发更大规模的模型做准备",90106,"2026-04-06T11:19:32",[35,15,13,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":72,"owner_name":73,"owner_avatar_url":74,"owner_bio":75,"owner_company":76,"owner_location":76,"owner_email":77,"owner_twitter":78,"owner_website":79,"owner_url":80,"languages":81,"stars":105,"forks":106,"last_commit_at":107,"license":108,"difficulty_score":32,"env_os":109,"env_gpu":110,"env_ram":110,"env_deps":111,"category_tags":116,"github_topics":117,"view_count":32,"oss_zip_url":76,"oss_zip_packed_at":76,"status":17,"created_at":128,"updated_at":129,"faqs":130,"releases":160},5367,"microsoft\u002FAI-For-Beginners","AI-For-Beginners","12 Weeks, 24 Lessons, AI for All!","AI-For-Beginners 是由微软推出的一套系统化人工智能入门课程，旨在帮助零基础用户轻松跨越 AI 学习门槛。面对人工智能领域知识繁杂、上手难度大的痛点，这套资源提供了结构清晰的学习路径，将复杂的概念拆解为易于消化的内容。\n\n该课程专为初学者设计，无论是希望转行进入科技领域的学生、想要拓展技能树的开发者，还是对 AI 原理充满好奇的普通爱好者，都能从中受益。它不需要你具备高深的数学背景或编程经验，只需跟随节奏即可循序渐进地掌握核心知识。\n\n在内容安排上，AI-For-Beginners 规划了为期 12 周、共 24 节课的完整大纲。课程不仅涵盖 TensorFlow 和 PyTorch 等主流框架的实战演练，还特别纳入了人工智能伦理等重要议题，确保学习者既能动手构建模型，又能理解技术背后的社会责任。此外，项目支持包括简体中文在内的全球数十种语言，并通过 GitHub 社区保持内容的持续更新与互动。配合丰富的测验、实验环节以及可视化的学习笔记，AI-For-Beginners 让探索人工智能世界变得既有趣又高效。","[![GitHub license](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002FLICENSE)\n[![GitHub contributors](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fgraphs\u002Fcontributors\u002F)\n[![GitHub issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F)\n[![GitHub pull-requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fpulls\u002F)\n[![PRs Welcome](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPRs-welcome-brightgreen.svg?style=flat-square)](http:\u002F\u002Fmakeapullrequest.com)\n\n[![GitHub watchers](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fwatchers\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Watch)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fwatchers\u002F)\n[![GitHub forks](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Fork)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fnetwork\u002F)\n[![GitHub stars](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Star)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fstargazers\u002F)\n[![Binder](https:\u002F\u002Fmybinder.org\u002Fbadge_logo.svg)](https:\u002F\u002Fmybinder.org\u002Fv2\u002Fgh\u002Fmicrosoft\u002Fai-for-beginners\u002FHEAD)\n[![Gitter](https:\u002F\u002Fbadges.gitter.im\u002FMicrosoft\u002Fai-for-beginners.svg)](https:\u002F\u002Fgitter.im\u002FMicrosoft\u002Fai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)\n\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\n# Artificial Intelligence for Beginners - A Curriculum\n\n|![Sketchnote by @girlie_mac https:\u002F\u002Ftwitter.com\u002Fgirlie_mac](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fmicrosoft_AI-For-Beginners_readme_7206f99da5c2.png)|\n|:---:|\n| AI For Beginners - _Sketchnote by [@girlie_mac](https:\u002F\u002Ftwitter.com\u002Fgirlie_mac)_ |\n\nExplore 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\n\n\n### 🌐 Multi-Language Support\n\n#### Supported via GitHub Action (Automated & Always Up-to-Date)\n\n\u003C!-- CO-OP TRANSLATOR LANGUAGES TABLE START -->\n[Arabic](.\u002Ftranslations\u002Far\u002FREADME.md) | [Bengali](.\u002Ftranslations\u002Fbn\u002FREADME.md) | [Bulgarian](.\u002Ftranslations\u002Fbg\u002FREADME.md) | [Burmese (Myanmar)](.\u002Ftranslations\u002Fmy\u002FREADME.md) | [Chinese (Simplified)](.\u002Ftranslations\u002Fzh-CN\u002FREADME.md) | [Chinese (Traditional, Hong Kong)](.\u002Ftranslations\u002Fzh-HK\u002FREADME.md) | [Chinese (Traditional, Macau)](.\u002Ftranslations\u002Fzh-MO\u002FREADME.md) | [Chinese (Traditional, Taiwan)](.\u002Ftranslations\u002Fzh-TW\u002FREADME.md) | [Croatian](.\u002Ftranslations\u002Fhr\u002FREADME.md) | [Czech](.\u002Ftranslations\u002Fcs\u002FREADME.md) | [Danish](.\u002Ftranslations\u002Fda\u002FREADME.md) | [Dutch](.\u002Ftranslations\u002Fnl\u002FREADME.md) | [Estonian](.\u002Ftranslations\u002Fet\u002FREADME.md) | [Finnish](.\u002Ftranslations\u002Ffi\u002FREADME.md) | [French](.\u002Ftranslations\u002Ffr\u002FREADME.md) | [German](.\u002Ftranslations\u002Fde\u002FREADME.md) | [Greek](.\u002Ftranslations\u002Fel\u002FREADME.md) | [Hebrew](.\u002Ftranslations\u002Fhe\u002FREADME.md) | [Hindi](.\u002Ftranslations\u002Fhi\u002FREADME.md) | [Hungarian](.\u002Ftranslations\u002Fhu\u002FREADME.md) | [Indonesian](.\u002Ftranslations\u002Fid\u002FREADME.md) | [Italian](.\u002Ftranslations\u002Fit\u002FREADME.md) | [Japanese](.\u002Ftranslations\u002Fja\u002FREADME.md) | [Kannada](.\u002Ftranslations\u002Fkn\u002FREADME.md) | [Korean](.\u002Ftranslations\u002Fko\u002FREADME.md) | [Lithuanian](.\u002Ftranslations\u002Flt\u002FREADME.md) | [Malay](.\u002Ftranslations\u002Fms\u002FREADME.md) | [Malayalam](.\u002Ftranslations\u002Fml\u002FREADME.md) | [Marathi](.\u002Ftranslations\u002Fmr\u002FREADME.md) | [Nepali](.\u002Ftranslations\u002Fne\u002FREADME.md) | [Nigerian Pidgin](.\u002Ftranslations\u002Fpcm\u002FREADME.md) | [Norwegian](.\u002Ftranslations\u002Fno\u002FREADME.md) | [Persian (Farsi)](.\u002Ftranslations\u002Ffa\u002FREADME.md) | [Polish](.\u002Ftranslations\u002Fpl\u002FREADME.md) | [Portuguese (Brazil)](.\u002Ftranslations\u002Fpt-BR\u002FREADME.md) | [Portuguese (Portugal)](.\u002Ftranslations\u002Fpt-PT\u002FREADME.md) | [Punjabi (Gurmukhi)](.\u002Ftranslations\u002Fpa\u002FREADME.md) | [Romanian](.\u002Ftranslations\u002Fro\u002FREADME.md) | [Russian](.\u002Ftranslations\u002Fru\u002FREADME.md) | [Serbian (Cyrillic)](.\u002Ftranslations\u002Fsr\u002FREADME.md) | [Slovak](.\u002Ftranslations\u002Fsk\u002FREADME.md) | [Slovenian](.\u002Ftranslations\u002Fsl\u002FREADME.md) | [Spanish](.\u002Ftranslations\u002Fes\u002FREADME.md) | [Swahili](.\u002Ftranslations\u002Fsw\u002FREADME.md) | [Swedish](.\u002Ftranslations\u002Fsv\u002FREADME.md) | [Tagalog (Filipino)](.\u002Ftranslations\u002Ftl\u002FREADME.md) | [Tamil](.\u002Ftranslations\u002Fta\u002FREADME.md) | [Telugu](.\u002Ftranslations\u002Fte\u002FREADME.md) | [Thai](.\u002Ftranslations\u002Fth\u002FREADME.md) | [Turkish](.\u002Ftranslations\u002Ftr\u002FREADME.md) | [Ukrainian](.\u002Ftranslations\u002Fuk\u002FREADME.md) | [Urdu](.\u002Ftranslations\u002Fur\u002FREADME.md) | [Vietnamese](.\u002Ftranslations\u002Fvi\u002FREADME.md)\n\n> **Prefer to Clone Locally?**\n>\n> This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:\n>\n> **Bash \u002F macOS \u002F Linux:**\n> ```bash\n> git clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\n> cd AI-For-Beginners\n> git sparse-checkout set --no-cone '\u002F*' '!translations' '!translated_images'\n> ```\n>\n> **CMD (Windows):**\n> ```cmd\n> git clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\n> cd AI-For-Beginners\n> git sparse-checkout set --no-cone \"\u002F*\" \"!translations\" \"!translated_images\"\n> ```\n>\n> This gives you everything you need to complete the course with a much faster download.\n\u003C!-- CO-OP TRANSLATOR LANGUAGES TABLE END -->\n\n**If you wish to have additional translations languages supported are listed [here](https:\u002F\u002Fgithub.com\u002FAzure\u002Fco-op-translator\u002Fblob\u002Fmain\u002Fgetting_started\u002Fsupported-languages.md)**\n\n## Join the Community\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\n## What you will learn\n\n**[Mindmap of the Course](http:\u002F\u002Fsoshnikov.com\u002Fcourses\u002Fai-for-beginners\u002Fmindmap.html)**\n\nIn this curriculum, you will learn:\n\n* Different approaches to Artificial Intelligence, including the \"good old\" symbolic approach with **Knowledge Representation** and reasoning ([GOFAI](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSymbolic_artificial_intelligence)).\n* **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](http:\u002F\u002FTensorflow.org) and [PyTorch](http:\u002F\u002Fpytorch.org).\n* **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.\n* Less popular AI approaches, such as **Genetic Algorithms** and **Multi-Agent Systems**.\n\nWhat we will not cover in this curriculum:\n\n> [Find all additional resources for this course in our Microsoft Learn collection](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)\n\n* Business cases of using **AI in Business**. Consider taking [Introduction to AI for business users](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fintroduction-ai-for-business-users\u002F?WT.mc_id=academic-77998-bethanycheum) learning path on Microsoft Learn, or [AI Business School](https:\u002F\u002Fwww.microsoft.com\u002Fai\u002Fai-business-school\u002F?WT.mc_id=academic-77998-bethanycheum), developed in cooperation with [INSEAD](https:\u002F\u002Fwww.insead.edu\u002F).\n* **Classic Machine Learning**, which is well described in our [Machine Learning for Beginners Curriculum](http:\u002F\u002Fgithub.com\u002FMicrosoft\u002FML-for-Beginners).\n* Practical AI applications built using **[Cognitive Services](https:\u002F\u002Fazure.microsoft.com\u002Fservices\u002Fcognitive-services\u002F?WT.mc_id=academic-77998-bethanycheum)**. For this, we recommend that you start with modules Microsoft Learn for [vision](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fcreate-computer-vision-solutions-azure-cognitive-services\u002F?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fexplore-natural-language-processing\u002F?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fpaths\u002Fdevelop-ai-solutions-azure-openai\u002F?WT.mc_id=academic-77998-bethanycheum)** and others.\n* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https:\u002F\u002Fazure.microsoft.com\u002Fservices\u002Fmachine-learning\u002F?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fpaths\u002Fget-started-fabric\u002F?WT.mc_id=academic-77998-bethanycheum), or [Azure Databricks](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fdata-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Consider using [Build and operate machine learning solutions with Azure Machine Learning](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fbuild-ai-solutions-with-azure-ml-service\u002F?WT.mc_id=academic-77998-bethanycheum) and [Build and Operate Machine Learning Solutions with Azure Databricks](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fbuild-operate-machine-learning-solutions-azure-databricks\u002F?WT.mc_id=academic-77998-bethanycheum) learning paths.\n* **Conversational AI** and **Chat Bots**. There is a separate [Create conversational AI solutions](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fcreate-conversational-ai-solutions\u002F?WT.mc_id=academic-77998-bethanycheum) learning path, and you can also refer to [this blog post](https:\u002F\u002Fsoshnikov.com\u002Fazure\u002Fhello-bot-conversational-ai-on-microsoft-platform\u002F) for more detail.\n* **Deep Mathematics** behind deep learning. For this, we would recommend [Deep Learning](https:\u002F\u002Fwww.amazon.com\u002FDeep-Learning-Adaptive-Computation-Machine\u002Fdp\u002F0262035618) by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at [https:\u002F\u002Fwww.deeplearningbook.org\u002F](https:\u002F\u002Fwww.deeplearningbook.org\u002F).\n\nFor a gentle introduction to _AI in the Cloud_ topics you may consider taking the [Get started with artificial intelligence on Azure](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fget-started-with-artificial-intelligence-on-azure\u002F?WT.mc_id=academic-77998-bethanycheum) Learning Path.\n\n# Content\n\n|     |                                                                 Lesson Link                                                                  |                                           PyTorch\u002FKeras\u002FTensorFlow                                          | Lab                                                            |\n| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |\n| 0  |                                 [Course Setup](.\u002Flessons\u002F0-course-setup\u002Fsetup.md)                                 |                      [Setup Your Development Environment](.\u002Flessons\u002F0-course-setup\u002Fhow-to-run.md)                       |   |\n| I  |               [**Introduction to AI**](.\u002Flessons\u002F1-Intro\u002FREADME.md)      | | |\n| 01  |       [Introduction and History of AI](.\u002Flessons\u002F1-Intro\u002FREADME.md)       |           -                            | -  |\n| II |              **Symbolic AI**              |\n| 02  |       [Knowledge Representation and Expert Systems](.\u002Flessons\u002F2-Symbolic\u002FREADME.md)       |            [Expert Systems](.\u002Flessons\u002F2-Symbolic\u002FAnimals.ipynb) \u002F  [Ontology](.\u002Flessons\u002F2-Symbolic\u002FFamilyOntology.ipynb) \u002F[Concept Graph](.\u002Flessons\u002F2-Symbolic\u002FMSConceptGraph.ipynb)                             |  |\n| III |                        [**Introduction to Neural Networks**](.\u002Flessons\u002F3-NeuralNetworks\u002FREADME.md) |||\n| 03  |                [Perceptron](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002FREADME.md)                 |                       [Notebook](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002FPerceptron.ipynb)                      | [Lab](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002Flab\u002FREADME.md) |\n| 04  |                   [Multi-Layered Perceptron and Creating our own Framework](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002FREADME.md)                   |        [Notebook](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002FOwnFramework.ipynb)        | [Lab](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002Flab\u002FREADME.md) |\n| 05  |            [Intro to Frameworks (PyTorch\u002FTensorFlow) and Overfitting](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroPyTorch.ipynb) \u002F [Keras](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKeras.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKerasTF.ipynb)             | [Lab](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002Flab\u002FREADME.md) |\n| IV  |            [**Computer Vision**](.\u002Flessons\u002F4-ComputerVision\u002FREADME.md)             | [PyTorch](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-computer-vision-pytorch\u002F?WT.mc_id=academic-77998-cacaste) \u002F [TensorFlow](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-computer-vision-TensorFlow\u002F?WT.mc_id=academic-77998-cacaste)| [Explore Computer Vision on Microsoft Azure](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |\n| 06  |            [Intro to Computer Vision. OpenCV](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002FREADME.md)             |           [Notebook](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002FOpenCV.ipynb)         | [Lab](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002Flab\u002FREADME.md) |\n| 07  |            [Convolutional Neural Networks](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FREADME.md) &  [CNN Architectures](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FCNN_Architectures.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FConvNetsPyTorch.ipynb) \u002F[TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FConvNetsTF.ipynb)             | [Lab](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002Flab\u002FREADME.md) |\n| 08  |            [Pre-trained Networks and Transfer Learning](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FREADME.md) and [Training Tricks](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FTrainingTricks.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FTransferLearningPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKerasTF.ipynb)             | [Lab](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002Flab\u002FREADME.md) |\n| 09  |            [Autoencoders and VAEs](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FAutoEncodersPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FAutoencodersTF.ipynb)             |  |\n| 10  |            [Generative Adversarial Networks & Artistic Style Transfer](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FGANPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FGANTF.ipynb)             |  |\n| 11  |            [Object Detection](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002FREADME.md)             |         [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002FObjectDetection.ipynb)             | [Lab](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002Flab\u002FREADME.md) |\n| 12  |            [Semantic Segmentation. U-Net](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FSemanticSegmentationPytorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FSemanticSegmentationTF.ipynb)             |  |\n| V  |            [**Natural Language Processing**](.\u002Flessons\u002F5-NLP\u002FREADME.md)             | [PyTorch](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-natural-language-processing-pytorch\u002F?WT.mc_id=academic-77998-cacaste) \u002F[TensorFlow](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-natural-language-processing-TensorFlow\u002F?WT.mc_id=academic-77998-cacaste) | [Explore Natural Language Processing on Microsoft Azure](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|\n| 13  |            [Text Representation. Bow\u002FTF-IDF](.\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FTextRepresentationPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FTextRepresentationTF.ipynb)             | |\n| 14  |            [Semantic word embeddings. Word2Vec and GloVe](.\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FEmbeddingsPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FEmbeddingsTF.ipynb)             |  |\n| 15  |            [Language Modeling. Training your own embeddings](.\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FCBoW-PyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FCBoW-TF.ipynb)             | [Lab](.\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002Flab\u002FREADME.md) |\n| 16  |            [Recurrent Neural Networks](.\u002Flessons\u002F5-NLP\u002F16-RNN\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F16-RNN\u002FRNNPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F16-RNN\u002FRNNTF.ipynb)             |  |\n| 17  |            [Generative Recurrent Networks](.\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FGenerativePyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FGenerativeTF.ipynb)             | [Lab](.\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002Flab\u002FREADME.md) |\n| 18  |            [Transformers. BERT.](.\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FTransformersPyTorch.ipynb) \u002F[TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FTransformersTF.ipynb)             |  |\n| 19  |            [Named Entity Recognition](.\u002Flessons\u002F5-NLP\u002F19-NER\u002FREADME.md)             |           [TensorFlow](https:\u002F\u002Fmicrosoft.github.io\u002FAI-For-Beginners\u002Flessons\u002F5-NLP\u002F19-NER\u002FNER-TF.ipynb)             | [Lab](.\u002Flessons\u002F5-NLP\u002F19-NER\u002Flab\u002FREADME.md) |\n| 20  |            [Large Language Models, Prompt Programming and Few-Shot Tasks](.\u002Flessons\u002F5-NLP\u002F20-LangModels\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fmicrosoft.github.io\u002FAI-For-Beginners\u002Flessons\u002F5-NLP\u002F20-LangModels\u002FGPT-PyTorch.ipynb) | |\n| VI |            **Other AI Techniques** || |\n| 21  |            [Genetic Algorithms](.\u002Flessons\u002F6-Other\u002F21-GeneticAlgorithms\u002FREADME.md)             |           [Notebook](.\u002Flessons\u002F6-Other\u002F21-GeneticAlgorithms\u002FGenetic.ipynb) | |\n| 22  |            [Deep Reinforcement Learning](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FCartPole-RL-PyTorch.ipynb) \u002F[TensorFlow](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FCartPole-RL-TF.ipynb)             | [Lab](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002Flab\u002FREADME.md) |\n| 23  |            [Multi-Agent Systems](.\u002Flessons\u002F6-Other\u002F23-MultiagentSystems\u002FREADME.md)             |  | |\n| VII |            **AI Ethics** | | |\n| 24  |            [AI Ethics and Responsible AI](.\u002Flessons\u002F7-Ethics\u002FREADME.md)             |           [Microsoft Learn: Responsible AI Principles](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fresponsible-ai-business-principles\u002F?WT.mc_id=academic-77998-cacaste) | |\n| IX  |            **Extras** | | |\n| 25  |            [Multi-Modal Networks, CLIP and VQGAN](.\u002Flessons\u002FX-Extras\u002FX1-MultiModal\u002FREADME.md)             |           [Notebook](.\u002Flessons\u002FX-Extras\u002FX1-MultiModal\u002FClip.ipynb)    | |\n\n## Each lesson contains\n\n* Pre-reading material\n* 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).\n* **Labs** available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem.\n* Some sections contain links to [**MS Learn**](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules that cover related topics.\n\n## Getting Started\n\n### 🎯 New to AI? Start Here!\n\nIf you're completely new to AI and want quick, hands-on examples, check out our [**Beginner-Friendly Examples**](.\u002Fexamples\u002FREADME.md)! These include:\n\n- 🌟 **Hello AI World** - Your first AI program (pattern recognition)\n- 🧠 **Simple Neural Network** - Build a neural network from scratch  \n- 🖼️ **Image Classifier** - Classify images with detailed comments\n- 💬 **Text Sentiment** - Analyze positive\u002Fnegative text\n\nThese examples are designed to help you understand AI concepts before diving into the full curriculum.\n\n### 📚 Full Curriculum Setup\n\n- We have created a [setup lesson](.\u002Flessons\u002F0-course-setup\u002Fsetup.md) to help you with setting up your development environment. - For Educators, we have created a [curricula setup lesson](.\u002Flessons\u002F0-course-setup\u002Ffor-teachers.md) for you too!\n- How to [Run the code in a VSCode or a Codespace](.\u002Flessons\u002F0-course-setup\u002Fhow-to-run.md)\n\nFollow these steps:\n\nFork the Repository: Click on the \"Fork\" button at the top-right corner of this page.\n\nClone the Repository: `git clone https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git`\n\nDon't forget to star (🌟) this repo to find it easier later.\n\n## Meet other Learners\n\nJoin our [official AI Discord server](https:\u002F\u002Faka.ms\u002Fgenai-discord?WT.mc_id=academic-105485-bethanycheum) to meet and network with other learners taking this course and get support.\n\nIf you have product feedback or questions whilst building visit our [Azure AI Foundry Developer Forum](https:\u002F\u002Faka.ms\u002Ffoundry\u002Fforum)\n\n## Quizzes \n\n> **A note about quizzes**: All quizzes are contained in the Quiz-app folder in etc\\quiz-app, or [Online Here](https:\u002F\u002Fff-quizzes.netlify.app\u002F) 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.\n\n## Help Wanted\n\nDo you have suggestions or found spelling or code errors? Raise an issue or create a pull request.\n\n## Special Thanks\n\n* **✍️ Primary Author:** [Dmitry Soshnikov](http:\u002F\u002Fsoshnikov.com), PhD\n* **🔥 Editor:** [Jen Looper](https:\u002F\u002Ftwitter.com\u002Fjenlooper), PhD\n* **🎨 Sketchnote illustrator:** [Tomomi Imura](https:\u002F\u002Ftwitter.com\u002Fgirlie_mac)\n* **✅ Quiz Creator:** [Lateefah Bello](https:\u002F\u002Fgithub.com\u002FCinnamonXI), [MLSA](https:\u002F\u002Fstudentambassadors.microsoft.com\u002F)\n* **🙏 Core Contributors:** [Evgenii Pishchik](https:\u002F\u002Fgithub.com\u002FPe4enIks)\n\n## Other Curricula\n\nOur team produces other curricula! Check out:\n\n\u003C!-- CO-OP TRANSLATOR OTHER COURSES START -->\n### LangChain\n[![LangChain4j for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Faka.ms\u002Flangchain4j-for-beginners)\n[![LangChain.js for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Faka.ms\u002Flangchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin)\n[![LangChain for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Flangchain-for-beginners?WT.mc_id=m365-94501-dwahlin)\n---\n\n### Azure \u002F Edge \u002F MCP \u002F Agents\n[![AZD for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAZD-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![Edge AI for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEdge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fedgeai-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![MCP for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fmcp-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![AI Agents for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fai-agents-for-beginners?WT.mc_id=academic-105485-koreyst)\n\n---\n \n### Generative AI Series\n[![Generative AI for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![Generative AI (.NET)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FGenerative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst)\n[![Generative AI (Java)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst)\n[![Generative AI (JavaScript)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-with-javascript?WT.mc_id=academic-105485-koreyst)\n\n---\n \n### Core Learning\n[![ML for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https:\u002F\u002Faka.ms\u002Fml-beginners?WT.mc_id=academic-105485-koreyst)\n[![Data Science for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FData%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https:\u002F\u002Faka.ms\u002Fdatascience-beginners?WT.mc_id=academic-105485-koreyst)\n[![AI for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https:\u002F\u002Faka.ms\u002Fai-beginners?WT.mc_id=academic-105485-koreyst)\n[![Cybersecurity for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FSecurity-101?WT.mc_id=academic-96948-sayoung)\n[![Web Dev for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWeb%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https:\u002F\u002Faka.ms\u002Fwebdev-beginners?WT.mc_id=academic-105485-koreyst)\n[![IoT for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https:\u002F\u002Faka.ms\u002Fiot-beginners?WT.mc_id=academic-105485-koreyst)\n[![XR Development for Beginners](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FXR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fxr-development-for-beginners?WT.mc_id=academic-105485-koreyst)\n\n---\n \n### Copilot Series\n[![Copilot for AI Paired Programming](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https:\u002F\u002Faka.ms\u002FGitHubCopilotAI?WT.mc_id=academic-105485-koreyst)\n[![Copilot for C#\u002F.NET](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20for%20C%23\u002F.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fmastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst)\n[![Copilot Adventure](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FCopilotAdventures?WT.mc_id=academic-105485-koreyst)\n\u003C!-- CO-OP TRANSLATOR OTHER COURSES END -->\n\n## Getting Help\n\nIf 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.\n\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\nIf you have product feedback or errors while building visit:\n\n[![Microsoft Foundry Developer Forum](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https:\u002F\u002Faka.ms\u002Ffoundry\u002Fforum)\n","[![GitHub 许可证](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002FLICENSE)\n[![GitHub 贡献者](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fgraphs\u002Fcontributors\u002F)\n[![GitHub 问题](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F)\n[![GitHub 拉取请求](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fmicrosoft\u002FAI-For-Beginners.svg)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fpulls\u002F)\n[![欢迎提交 PR](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPRs-welcome-brightgreen.svg?style=flat-square)](http:\u002F\u002Fmakeapullrequest.com)\n\n[![GitHub 监视者](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fwatchers\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Watch)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fwatchers\u002F)\n[![GitHub 分支](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Fork)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fnetwork\u002F)\n[![GitHub 星标](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fmicrosoft\u002FAI-For-Beginners.svg?style=social&label=Star)](https:\u002F\u002FGitHub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fstargazers\u002F)\n[![Binder](https:\u002F\u002Fmybinder.org\u002Fbadge_logo.svg)](https:\u002F\u002Fmybinder.org\u002Fv2\u002Fgh\u002Fmicrosoft\u002Fai-for-beginners\u002FHEAD)\n[![Gitter](https:\u002F\u002Fbadges.gitter.im\u002FMicrosoft\u002Fai-for-beginners.svg)](https:\u002F\u002Fgitter.im\u002FMicrosoft\u002Fai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)\n\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\n# 面向初学者的人工智能——课程体系\n\n|![由 @girlie_mac 绘制的速写笔记 https:\u002F\u002Ftwitter.com\u002Fgirlie_mac](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fmicrosoft_AI-For-Beginners_readme_7206f99da5c2.png)|\n|:---:|\n| 面向初学者的人工智能 - _速写笔记由 [@girlie_mac](https:\u002F\u002Ftwitter.com\u002Fgirlie_mac) 绘制_ |\n\n通过我们的12周、24课时课程体系，探索**人工智能**（AI）的世界吧！课程包含实用的课程内容、测验和实验。该课程对初学者友好，涵盖了TensorFlow、PyTorch等工具，以及人工智能伦理等内容。\n\n\n### 🌐 多语言支持\n\n#### 由 GitHub Action 自动化支持，始终保持最新\n\n\u003C!-- 合作翻译语言表格开始 -->\n阿拉伯语](.\u002Ftranslations\u002Far\u002FREADME.md) | [孟加拉语](.\u002Ftranslations\u002Fbn\u002FREADME.md) | [保加利亚语](.\u002Ftranslations\u002Fbg\u002FREADME.md) | [缅甸语](.\u002Ftranslations\u002Fmy\u002FREADME.md) | [简体中文](.\u002Ftranslations\u002Fzh-CN\u002FREADME.md) | [繁体中文（香港）](.\u002Ftranslations\u002Fzh-HK\u002FREADME.md) | [繁体中文（澳门）](.\u002Ftranslations\u002Fzh-MO\u002FREADME.md) | [繁体中文（台湾）](.\u002Ftranslations\u002Fzh-TW\u002FREADME.md) | [克罗地亚语](.\u002Ftranslations\u002Fhr\u002FREADME.md) | [捷克语](.\u002Ftranslations\u002Fcs\u002FREADME.md) | [丹麦语](.\u002Ftranslations\u002Fda\u002FREADME.md) | [荷兰语](.\u002Ftranslations\u002Fnl\u002FREADME.md) | [爱沙尼亚语](.\u002Ftranslations\u002Fet\u002FREADME.md) | [芬兰语](.\u002Ftranslations\u002Ffi\u002FREADME.md) | [法语](.\u002Ftranslations\u002Ffr\u002FREADME.md) | [德语](.\u002Ftranslations\u002Fde\u002FREADME.md) | [希腊语](.\u002Ftranslations\u002Fel\u002FREADME.md) | [希伯来语](.\u002Ftranslations\u002Fhe\u002FREADME.md) | [印地语](.\u002Ftranslations\u002Fhi\u002FREADME.md) | [匈牙利语](.\u002Ftranslations\u002Fhu\u002FREADME.md) | [印尼语](.\u002Ftranslations\u002Fid\u002FREADME.md) | [意大利语](.\u002Ftranslations\u002Fit\u002FREADME.md) | [日语](.\u002Ftranslations\u002Fja\u002FREADME.md) | [坎纳达语](.\u002Ftranslations\u002Fkn\u002FREADME.md) | [韩语](.\u002Ftranslations\u002Fko\u002FREADME.md) | [立陶宛语](.\u002Ftranslations\u002Flt\u002FREADME.md) | [马来语](.\u002Ftranslations\u002Fms\u002FREADME.md) | [马拉雅拉姆语](.\u002Ftranslations\u002Fml\u002FREADME.md) | [马拉地语](.\u002Ftranslations\u002Fmr\u002FREADME.md) | [尼泊尔语](.\u002Ftranslations\u002Fne\u002FREADME.md) | [尼日利亚皮钦语](.\u002Ftranslations\u002Fpcm\u002FREADME.md) | [挪威语](.\u002Ftranslations\u002Fno\u002FREADME.md) | [波斯语（法语）](.\u002Ftranslations\u002Ffa\u002FREADME.md) | [波兰语](.\u002Ftranslations\u002Fpl\u002FREADME.md) | [巴西葡萄牙语](.\u002Ftranslations\u002Fpt-BR\u002FREADME.md) | [葡萄牙语（葡萄牙）](.\u002Ftranslations\u002Fpt-PT\u002FREADME.md) | [旁遮普语（古鲁穆基文）](.\u002Ftranslations\u002Fpa\u002FREADME.md) | [罗马尼亚语](.\u002Ftranslations\u002Fro\u002FREADME.md) | [俄语](.\u002Ftranslations\u002Fru\u002FREADME.md) | [塞尔维亚语（西里尔字母）](.\u002Ftranslations\u002Fsr\u002FREADME.md) | [斯洛伐克语](.\u002Ftranslations\u002Fsk\u002FREADME.md) | [斯洛文尼亚语](.\u002Ftranslations\u002Fsl\u002FREADME.md) | [西班牙语](.\u002Ftranslations\u002Fes\u002FREADME.md) | [斯瓦希里语](.\u002Ftranslations\u002Fsw\u002FREADME.md) | [瑞典语](.\u002Ftranslations\u002Fsv\u002FREADME.md) | [塔加路语（菲律宾语）](.\u002Ftranslations\u002Ftl\u002FREADME.md) | [泰米尔语](.\u002Ftranslations\u002Fta\u002FREADME.md) | [泰卢固语](.\u002Ftranslations\u002Fte\u002FREADME.md) | [泰语](.\u002Ftranslations\u002Fth\u002FREADME.md) | [土耳其语](.\u002Ftranslations\u002Ftr\u002FREADME.md) | [乌克兰语](.\u002Ftranslations\u002Fuk\u002FREADME.md) | [乌尔都语](.\u002Ftranslations\u002Fur\u002FREADME.md) | [越南语](.\u002Ftranslations\u002Fvi\u002FREADME.md)\n\n> **更倾向于本地克隆吗？**\n>\n> 此仓库包含50多种语言的翻译，这会显著增加下载大小。若想不下载翻译内容而进行克隆，请使用稀疏检出功能：\n>\n> **Bash \u002F macOS \u002F Linux：**\n> ```bash\n> git clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\n> cd AI-For-Beginners\n> git sparse-checkout set --no-cone '\u002F*' '!translations' '!translated_images'\n> ```\n>\n> **CMD（Windows）：**\n> ```cmd\n> git clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\n> cd AI-For-Beginners\n> git sparse-checkout set --no-cone \"\u002F*\" \"!translations\" \"!translated_images\"\n> ```\n>\n> 这样你就能获得完成课程所需的一切，同时下载速度也会快很多。\n\u003C!-- 合作翻译语言表格结束 -->\n\n**如果您希望支持更多语言的翻译，可在[这里](https:\u002F\u002Fgithub.com\u002FAzure\u002Fco-op-translator\u002Fblob\u002Fmain\u002Fgetting_started\u002Fsupported-languages.md)查看支持的语言列表。**\n\n## 加入社区\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\n## 你将学到的内容\n\n**[课程思维导图](http:\u002F\u002Fsoshnikov.com\u002Fcourses\u002Fai-for-beginners\u002Fmindmap.html)**\n\n在本课程中，你将学习：\n\n* 人工智能的不同方法，包括“老派”的符号主义方法，涉及**知识表示**和推理（[GOFAI](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSymbolic_artificial_intelligence)）。\n* **神经网络**和**深度学习**，它们是现代人工智能的核心。我们将使用两种最流行的框架——[TensorFlow](http:\u002F\u002FTensorflow.org)和[PyTorch](http:\u002F\u002Fpytorch.org)——通过代码来阐释这些重要主题背后的概念。\n* 用于处理图像和文本的**神经网络架构**。我们会介绍一些较新的模型，但可能不会涵盖最先进的技术。\n* 较不流行的人工智能方法，例如**遗传算法**和**多智能体系统**。\n\n本课程不会涵盖的内容：\n\n> [在此课程的所有附加资源可在我们的 Microsoft Learn 系列中找到](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)\n\n* **人工智能在商业中的应用案例**。建议你参加 Microsoft Learn 上的[面向业务用户的 AI 入门](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fintroduction-ai-for-business-users\u002F?WT.mc_id=academic-77998-bethanycheum)学习路径，或与[INSEAD](https:\u002F\u002Fwww.insead.edu\u002F)合作开发的[AI 商学院](https:\u002F\u002Fwww.microsoft.com\u002Fai\u002Fai-business-school\u002F?WT.mc_id=academic-77998-bethanycheum)。\n* **经典机器学习**，这在我们的[面向初学者的机器学习课程](http:\u002F\u002Fgithub.com\u002FMicrosoft\u002FML-for-Beginners)中有详细描述。\n* 使用**认知服务**构建的实际 AI 应用程序。为此，我们建议你从 Microsoft Learn 上的模块开始，例如[视觉](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fcreate-computer-vision-solutions-azure-cognitive-services\u002F?WT.mc_id=academic-77998-bethanycheum)、[自然语言处理](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fexplore-natural-language-processing\u002F?WT.mc_id=academic-77998-bethanycheum)、**使用 Azure OpenAI 服务的生成式 AI**以及其他内容。\n* 特定的 ML **云框架**，例如[Azure 机器学习](https:\u002F\u002Fazure.microsoft.com\u002Fservices\u002Fmachine-learning\u002F?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fpaths\u002Fget-started-fabric\u002F?WT.mc_id=academic-77998-bethanycheum)，或[Azure Databricks](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fdata-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建议你使用[使用 Azure 机器学习构建和运营机器学习解决方案](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fbuild-ai-solutions-with-azure-ml-service\u002F?WT.mc_id=academic-77998-bethanycheum)和[使用 Azure Databricks 构建和运营机器学习解决方案](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fbuild-operate-machine-learning-solutions-azure-databricks\u002F?WT.mc_id=academic-77998-bethanycheum)学习路径。\n* **对话式 AI**和**聊天机器人**。有一个专门的[创建对话式 AI 解决方案](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fcreate-conversational-ai-solutions\u002F?WT.mc_id=academic-77998-bethanycheum)学习路径，你也可以参考[这篇博客文章](https:\u002F\u002Fsoshnikov.com\u002Fazure\u002Fhello-bot-conversational-ai-on-microsoft-platform\u002F)以获取更多详细信息。\n* 深度学习背后的**深入数学理论**。对此，我们推荐 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 的《深度学习》，该书也可在线获取：[https:\u002F\u002Fwww.deeplearningbook.org\u002F](https:\u002F\u002Fwww.deeplearningbook.org\u002F)。\n\n如果你想温和地入门_云端人工智能_相关主题，可以考虑参加[在 Azure 上开始使用人工智能](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fget-started-with-artificial-intelligence-on-azure\u002F?WT.mc_id=academic-77998-bethanycheum)学习路径。\n\n# 内容\n\n|     |                                                                 课程链接                                                                  |                                           PyTorch\u002FKeras\u002FTensorFlow                                          | 实验                                                            |\n| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |\n| 0  |                                 [课程设置](.\u002Flessons\u002F0-course-setup\u002Fsetup.md)                                 |                      [设置你的开发环境](.\u002Flessons\u002F0-course-setup\u002Fhow-to-run.md)                       |   |\n| I  |               [**人工智能导论**](.\u002Flessons\u002F1-Intro\u002FREADME.md)      | | |\n| 01  |       [人工智能简介与历史](.\u002Flessons\u002F1-Intro\u002FREADME.md)       |           -                            | -  |\n| II |              **符号主义人工智能**              |\n| 02  |       [知识表示与专家系统](.\u002Flessons\u002F2-Symbolic\u002FREADME.md)       |            [专家系统](.\u002Flessons\u002F2-Symbolic\u002FAnimals.ipynb) \u002F  [本体](.\u002Flessons\u002F2-Symbolic\u002FFamilyOntology.ipynb) \u002F[概念图](.\u002Flessons\u002F2-Symbolic\u002FMSConceptGraph.ipynb)                             |  |\n| III |                        [**神经网络导论**](.\u002Flessons\u002F3-NeuralNetworks\u002FREADME.md) |||\n| 03  |                [感知机](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002FREADME.md)                 |                       [笔记本](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002FPerceptron.ipynb)                      | [实验](.\u002Flessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002Flab\u002FREADME.md) |\n| 04  |                   [多层感知机及自定义框架](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002FREADME.md)                   |        [笔记本](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002FOwnFramework.ipynb)        | [实验](.\u002Flessons\u002F3-NeuralNetworks\u002F04-OwnFramework\u002Flab\u002FREADME.md) |\n| 05  |            [框架简介（PyTorch\u002FTensorFlow）及过拟合](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroPyTorch.ipynb) \u002F [Keras](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKeras.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKerasTF.ipynb)             | [实验](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002Flab\u002FREADME.md) |\n| IV  |            [**计算机视觉**](.\u002Flessons\u002F4-ComputerVision\u002FREADME.md)             | [PyTorch](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-computer-vision-pytorch\u002F?WT.mc_id=academic-77998-cacaste) \u002F [TensorFlow](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-computer-vision-TensorFlow\u002F?WT.mc_id=academic-77998-cacaste)| [在微软 Azure 上探索计算机视觉](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |\n| 06  |            [计算机视觉简介。OpenCV](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002FREADME.md)             |           [笔记本](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002FOpenCV.ipynb)         | [实验](.\u002Flessons\u002F4-ComputerVision\u002F06-IntroCV\u002Flab\u002FREADME.md) |\n| 07  |            [卷积神经网络](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FREADME.md) &  [CNN 架构](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FCNN_Architectures.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FConvNetsPyTorch.ipynb) \u002F[TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002FConvNetsTF.ipynb)             | [实验](.\u002Flessons\u002F4-ComputerVision\u002F07-ConvNets\u002Flab\u002FREADME.md) |\n| 08  |            [预训练网络与迁移学习](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FREADME.md)和[训练技巧](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FTrainingTricks.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002FTransferLearningPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F3-NeuralNetworks\u002F05-Frameworks\u002FIntroKerasTF.ipynb)             | [实验](.\u002Flessons\u002F4-ComputerVision\u002F08-TransferLearning\u002Flab\u002FREADME.md) |\n| 09  |            [自编码器与变分自编码器](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FAutoEncodersPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F09-Autoencoders\u002FAutoencodersTF.ipynb)             |  |\n| 10  |            [生成对抗网络与艺术风格迁移](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FGANPyTorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F10-GANs\u002FGANTF.ipynb)             |  |\n| 11  |            [目标检测](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002FREADME.md)             |         [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002FObjectDetection.ipynb)             | [实验](.\u002Flessons\u002F4-ComputerVision\u002F11-ObjectDetection\u002Flab\u002FREADME.md) |\n| 12  |            [语义分割。U-Net](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FSemanticSegmentationPytorch.ipynb) \u002F [TensorFlow](.\u002Flessons\u002F4-ComputerVision\u002F12-Segmentation\u002FSemanticSegmentationTF.ipynb)             |  |\n| V  |            [**自然语言处理**](.\u002Flessons\u002F5-NLP\u002FREADME.md)             | [PyTorch](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-natural-language-processing-pytorch\u002F?WT.mc_id=academic-77998-cacaste) \u002F[TensorFlow](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fmodules\u002Fintro-natural-language-processing-TensorFlow\u002F?WT.mc_id=academic-77998-cacaste) | [在微软 Azure 上探索自然语言处理](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|\n| 13  |            [文本表示。词袋\u002FTF-IDF](.\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FTextRepresentationPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F13-TextRep\u002FTextRepresentationTF.ipynb)             | |\n| 14  |            [语义词嵌入。Word2Vec 和 GloVe](.\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FEmbeddingsPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F14-Embeddings\u002FEmbeddingsTF.ipynb)             |  |\n| 15  |            [语言建模。训练你自己的词嵌入](.\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FCBoW-PyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002FCBoW-TF.ipynb)             | [实验](.\u002Flessons\u002F5-NLP\u002F15-LanguageModeling\u002Flab\u002FREADME.md) |\n| 16  |            [循环神经网络](.\u002Flessons\u002F5-NLP\u002F16-RNN\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F16-RNN\u002FRNNPyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F16-RNN\u002FRNNTF.ipynb)             |  |\n| 17  |            [生成式循环神经网络](.\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FGenerativePyTorch.ipynb) \u002F [TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002FGenerativeTF.ipynb)             | [实验](.\u002Flessons\u002F5-NLP\u002F17-GenerativeNetworks\u002Flab\u002FREADME.md) |\n| 18  |            [Transformer。BERT。](.\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FTransformersPyTorch.ipynb) \u002F[TensorFlow](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fblob\u002Fmain\u002Flessons\u002F5-NLP\u002F18-Transformers\u002FTransformersTF.ipynb)             |  |\n| 19  |            [命名实体识别](.\u002Flessons\u002F5-NLP\u002F19-NER\u002FREADME.md)             |           [TensorFlow](https:\u002F\u002Fmicrosoft.github.io\u002FAI-For-Beginners\u002Flessons\u002F5-NLP\u002F19-NER\u002FNER-TF.ipynb)             | [实验](.\u002Flessons\u002F5-NLP\u002F19-NER\u002Flab\u002FREADME.md) |\n| 20  |            [大型语言模型、提示工程与少样本任务](.\u002Flessons\u002F5-NLP\u002F20-LangModels\u002FREADME.md)             |           [PyTorch](https:\u002F\u002Fmicrosoft.github.io\u002FAI-For-Beginners\u002Flessons\u002F5-NLP\u002F20-LangModels\u002FGPT-PyTorch.ipynb) | |\n| VI |            **其他人工智能技术** || |\n| 21  |            [遗传算法](.\u002Flessons\u002F6-Other\u002F21-GeneticAlgorithms\u002FREADME.md)             |           [笔记本](.\u002Flessons\u002F6-Other\u002F21-GeneticAlgorithms\u002FGenetic.ipynb) | |\n| 22  |            [深度强化学习](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FREADME.md)             |           [PyTorch](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FCartPole-RL-PyTorch.ipynb) \u002F[TensorFlow](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002FCartPole-RL-TF.ipynb)             | [实验](.\u002Flessons\u002F6-Other\u002F22-DeepRL\u002Flab\u002FREADME.md) |\n| 23  |            [多智能体系统](.\u002Flessons\u002F6-Other\u002F23-MultiagentSystems\u002FREADME.md)             |  | |\n| VII |            **人工智能伦理** | | |\n| 24  |            [人工智能伦理与负责任的人工智能](.\u002Flessons\u002F7-Ethics\u002FREADME.md)             |           [微软 Learn：负责任的 AI 原则](https:\u002F\u002Fdocs.microsoft.com\u002Flearn\u002Fpaths\u002Fresponsible-ai-business-principles\u002F?WT.mc_id=academic-77998-cacaste) | |\n| IX  |            **附加内容** | | |\n| 25  |            [多模态网络、CLIP 和 VQGAN](.\u002Flessons\u002FX-Extras\u002FX1-MultiModal\u002FREADME.md)             |           [笔记本](.\u002Flessons\u002FX-Extras\u002FX1-MultiModal\u002FClip.ipynb)    | |\n\n## 每节课包含\n\n* 阅读前材料\n* 可执行的 Jupyter 笔记本，这些笔记本通常针对特定的框架（**PyTorch** 或 **TensorFlow**）。可执行笔记本中也包含大量理论内容，因此要理解该主题，您需要至少完成一个版本的笔记本（无论是 PyTorch 还是 TensorFlow）。\n* 针对部分主题提供的**实验课**，让您有机会将所学知识应用于具体问题。\n* 部分章节包含指向 [**MS Learn**](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcollections\u002F7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模块的链接，这些模块涵盖了相关主题。\n\n## 开始学习\n\n### 🎯 刚接触 AI？从这里开始！\n\n如果您完全不了解 AI，并希望快速获得动手实践示例，请查看我们的[适合初学者的示例](.\u002Fexamples\u002FREADME.md)！其中包括：\n\n- 🌟 **Hello AI World** - 您的第一个 AI 程序（模式识别）\n- 🧠 **简单神经网络** - 从零构建神经网络\n- 🖼️ **图像分类器** - 带详细注释的图像分类\n- 💬 **文本情感分析** - 分析文本的正面或负面情绪\n\n这些示例旨在帮助您在深入完整课程之前理解 AI 的基本概念。\n\n### 📚 完整课程设置\n\n- 我们创建了一个[设置课程](.\u002Flessons\u002F0-course-setup\u002Fsetup.md)，以帮助您搭建开发环境。- 对于教育工作者，我们也为您准备了[课程设置课程](.\u002Flessons\u002F0-course-setup\u002Ffor-teachers.md)！\n- 如何在 VSCode 或 Codespace 中运行代码：[点击此处](.\u002Flessons\u002F0-course-setup\u002Fhow-to-run.md)\n\n请按照以下步骤操作：\n\n1. 分支仓库：点击页面右上角的“Fork”按钮。\n2. 克隆仓库：`git clone https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git`\n3. 不要忘记给这个仓库点个赞（🌟），以便日后更容易找到它。\n\n## 结识其他学习者\n\n加入我们的[官方 AI Discord 服务器](https:\u002F\u002Faka.ms\u002Fgenai-discord?WT.mc_id=academic-105485-bethanycheum)，与其他正在学习本课程的同学交流并获得支持。\n\n如果您在开发过程中有任何产品反馈或问题，请访问我们的[Azure AI Foundry 开发者论坛](https:\u002F\u002Faka.ms\u002Ffoundry\u002Fforum)。\n\n## 测验\n\n> **关于测验的说明**：所有测验都位于 etc\\quiz-app 文件夹中的 Quiz-app 文件夹内，或者可以在线访问[这里](https:\u002F\u002Fff-quizzes.netlify.app\u002F)。它们通过课程内的链接引用，Quiz-app 可以在本地运行，也可以部署到 Azure；请按照 `quiz-app` 文件夹中的说明进行操作。这些测验正在逐步本地化。\n\n## 欢迎提供帮助\n\n您是否有任何建议，或者发现了拼写或代码错误？请提交一个问题或创建一个拉取请求。\n\n## 特别致谢\n\n* **✍️ 主要作者：** [Dmitry Soshnikov](http:\u002F\u002Fsoshnikov.com)，博士\n* **🔥 编辑：** [Jen Looper](https:\u002F\u002Ftwitter.com\u002Fjenlooper)，博士\n* **🎨 思维导图插画师：** [Tomomi Imura](https:\u002F\u002Ftwitter.com\u002Fgirlie_mac)\n* **✅ 测验创建者：** [Lateefah Bello](https:\u002F\u002Fgithub.com\u002FCinnamonXI)，[MLSA](https:\u002F\u002Fstudentambassadors.microsoft.com\u002F)\n* **🙏 核心贡献者：** [Evgenii Pishchik](https:\u002F\u002Fgithub.com\u002FPe4enIks)\n\n## 其他课程\n\n我们的团队还制作了其他课程！请查看：\n\n\u003C!-- CO-OP TRANSLATOR OTHER COURSES START -->\n### LangChain\n[![LangChain4j 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Faka.ms\u002Flangchain4j-for-beginners)\n[![LangChain.js 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Faka.ms\u002Flangchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin)\n[![LangChain 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLangChain%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Flangchain-for-beginners?WT.mc_id=m365-94501-dwahlin)\n---\n\n### Azure \u002F Edge \u002F MCP \u002F Agents\n[![AZD 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAZD-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![Edge AI 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEdge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fedgeai-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![MCP 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fmcp-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![AI Agents 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fai-agents-for-beginners?WT.mc_id=academic-105485-koreyst)\n\n---\n \n### 生成式 AI 系列\n[![生成式 AI 初学者版](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-for-beginners?WT.mc_id=academic-105485-koreyst)\n[![生成式 AI (.NET)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FGenerative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst)\n[![生成式 AI (Java)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst)\n[![生成式 AI (JavaScript)](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGenerative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-with-javascript?WT.mc_id=academic-105485-koreyst)\n\n---\n\n### 核心学习\n[![面向初学者的机器学习](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https:\u002F\u002Faka.ms\u002Fml-beginners?WT.mc_id=academic-105485-koreyst)\n[![面向初学者的数据科学](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FData%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https:\u002F\u002Faka.ms\u002Fdatascience-beginners?WT.mc_id=academic-105485-koreyst)\n[![面向初学者的人工智能](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FAI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https:\u002F\u002Faka.ms\u002Fai-beginners?WT.mc_id=academic-105485-koreyst)\n[![面向初学者的网络安全](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FSecurity-101?WT.mc_id=academic-96948-sayoung)\n[![面向初学者的Web开发](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWeb%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https:\u002F\u002Faka.ms\u002Fwebdev-beginners?WT.mc_id=academic-105485-koreyst)\n[![面向初学者的物联网](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https:\u002F\u002Faka.ms\u002Fiot-beginners?WT.mc_id=academic-105485-koreyst)\n[![面向初学者的XR开发](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FXR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fxr-development-for-beginners?WT.mc_id=academic-105485-koreyst)\n\n---\n \n### Copilot系列\n[![用于AI结对编程的Copilot](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https:\u002F\u002Faka.ms\u002FGitHubCopilotAI?WT.mc_id=academic-105485-koreyst)\n[![适用于C#\u002F.NET的Copilot](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20for%20C%23\u002F.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fmastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst)\n[![Copilot冒险](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FCopilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FCopilotAdventures?WT.mc_id=academic-105485-koreyst)\n\u003C!-- CO-OP TRANSLATOR OTHER COURSES END -->\n\n## 获取帮助\n\n如果您在构建AI应用时遇到困难或有任何疑问，请加入MCP社区，与志同道合的学习者和经验丰富的开发者一起讨论。这是一个充满支持的社区，欢迎大家提问并自由分享知识。\n\n[![Microsoft Foundry Discord](https:\u002F\u002Fdcbadge.limes.pink\u002Fapi\u002Fserver\u002FnTYy5BXMWG)](https:\u002F\u002Fdiscord.gg\u002FnTYy5BXMWG)\n\n如果您在构建过程中遇到产品反馈或错误问题，请访问：\n\n[![Microsoft Foundry开发者论坛](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FGitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https:\u002F\u002Faka.ms\u002Ffoundry\u002Fforum)","# AI-For-Beginners 快速上手指南\n\n本指南帮助中国开发者快速开始微软开源的《AI 初学者》课程。该课程包含 12 周、24 节课，涵盖符号 AI、神经网络、深度学习（TensorFlow\u002FPyTorch）及 AI 伦理等内容。\n\n## 环境准备\n\n在开始之前，请确保您的开发环境满足以下要求：\n\n*   **操作系统**：Windows 10\u002F11, macOS, 或 Linux (Ubuntu\u002FCentOS 等)。\n*   **Python**：版本 3.8 或更高（推荐 3.9+）。\n    *   国内用户可使用清华源加速安装：[Python 下载](https:\u002F\u002Fmirrors.tuna.tsinghua.edu.cn\u002Fpython\u002F)\n*   **Git**：用于克隆代码仓库。\n*   **代码编辑器**：推荐安装 [Visual Studio Code](https:\u002F\u002Fcode.visualstudio.com\u002F) 并安装 Python 和 Jupyter 插件。\n*   **基础知识**：具备基本的 Python 编程能力。\n\n## 安装步骤\n\n### 1. 克隆仓库（推荐稀疏克隆）\n\n由于该仓库包含 50 多种语言的翻译文件，体积较大。建议仅下载核心课程内容以加快下载速度。\n\n**Linux \u002F macOS \u002F Git Bash (Windows):**\n```bash\ngit clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\ncd AI-For-Beginners\ngit sparse-checkout set --no-cone '\u002F*' '!translations' '!translated_images'\n```\n\n**Windows CMD:**\n```cmd\ngit clone --filter=blob:none --sparse https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners.git\ncd AI-For-Beginners\ngit sparse-checkout set --no-cone \"\u002F*\" \"!translations\" \"!translated_images\"\n```\n\n> **注意**：如果您需要中文文档，请在克隆后手动进入 `translations\u002Fzh-CN` 目录查看，或者不进行稀疏克隆直接下载完整版（速度较慢）。\n\n### 2. 配置虚拟环境与依赖\n\n进入项目目录并创建虚拟环境：\n\n```bash\ncd AI-For-Beginners\npython -m venv ai-env\n```\n\n激活虚拟环境：\n*   **Windows:** `ai-env\\Scripts\\activate`\n*   **macOS\u002FLinux:** `source ai-env\u002Fbin\u002Factivate`\n\n安装课程所需的依赖包。为了加速下载，建议使用国内镜像源（如清华源或阿里源）：\n\n```bash\n# 使用 pip 安装 requirements.txt (如果根目录有) 或按章节安装\n# 通常每个课程章节下都有独立的 requirements.txt，建议进入具体章节安装\n# 例如安装第一课的依赖：\npip install -r lessons\u002F1-Intro\u002Frequirements.txt -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n```\n\n*注：不同章节可能依赖不同的库（如 TensorFlow 或 PyTorch），请根据您正在学习的章节目录下的 `requirements.txt` 进行安装。*\n\n### 3. 验证环境\n\n确保 Jupyter Notebook 可用，以便运行课程中的 `.ipynb` 文件：\n\n```bash\npip install notebook -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\njupyter notebook\n```\n\n## 基本使用\n\n本课程主要通过 Jupyter Notebook 进行交互式学习。以下是开始第一节课的步骤：\n\n1.  **启动 Jupyter**：\n    在项目根目录下运行：\n    ```bash\n    jupyter notebook\n    ```\n    浏览器将自动打开本地服务页面。\n\n2.  **导航至课程**：\n    在浏览器界面中，依次进入 `lessons` -> `1-Intro` 文件夹。\n\n3.  **运行示例**：\n    点击打开 `README.md` 阅读理论，然后打开对应的 `.ipynb` 文件（如果有）。\n    \n    例如，在 **Lesson 3 (Neural Networks)** 中运行感知机示例：\n    ```bash\n    # 在终端中直接进入该目录运行（可选）\n    cd lessons\u002F3-NeuralNetworks\u002F03-Perceptron\n    jupyter notebook Perceptron.ipynb\n    ```\n\n4.  **执行代码**：\n    在 Notebook 界面中，选中代码单元格，按 `Shift + Enter` 运行代码，观察输出结果并完成课后练习（Lab）。\n\n### 替代方案：在线运行 (Binder)\n\n如果您不想在本地配置环境，可以直接通过 Binder 在浏览器中运行所有示例：\n\n[![Binder](https:\u002F\u002Fmybinder.org\u002Fbadge_logo.svg)](https:\u002F\u002Fmybinder.org\u002Fv2\u002Fgh\u002Fmicrosoft\u002Fai-for-beginners\u002FHEAD)\n\n点击上述链接即可加载完整环境并开始学习。","某高校计算机系的大二学生李明，计划从零开始学习人工智能并尝试开发一个图像分类项目，但面对庞杂的知识体系感到无从下手。\n\n### 没有 AI-For-Beginners 时\n- **学习路径混乱**：网上教程碎片化严重，李明花费数周在各类博客和视频中寻找资料，仍无法理清从基础数学到模型部署的完整逻辑。\n- **环境配置劝退**：试图直接上手 TensorFlow 或 PyTorch 时，因缺乏前置引导，频繁遭遇版本冲突和环境报错，导致还没写代码就信心受挫。\n- **理论与实践脱节**：看懂了公式推导却不知如何转化为代码，缺乏配套的实验室（Labs）环节，只能纸上谈兵。\n- **忽视伦理风险**：专注于算法实现，完全忽略了数据偏见和 AI 伦理等关键议题，为后续项目落地埋下隐患。\n\n### 使用 AI-For-Beginners 后\n- **结构化课程指引**：依托其\"12 周 24 课”的清晰大纲，李明按部就班地每周完成特定主题学习，迅速构建起完整的知识图谱。\n- **开箱即用的实验**：通过提供的 Jupyter Notebook 实战练习和 Binder 在线环境，他无需纠结本地配置，直接运行代码观察模型训练过程。\n- **学练测一体化**：每节课配套的测验和编程作业让他能即时验证理解程度，将抽象的数学原理快速转化为可运行的深度学习模型。\n- **全面素养提升**：课程中专门的伦理章节促使他在设计图像分类器时，主动考虑数据集的多样性，避免了算法歧视问题。\n\nAI-For-Beginners 将原本需要数月摸索的入门之路，压缩为一条清晰、可执行且兼顾技术与伦理的标准化成长通道。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fmicrosoft_AI-For-Beginners_7206f99d.png","microsoft","Microsoft","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fmicrosoft_4900709c.png","Open source projects and samples from Microsoft",null,"opensource@microsoft.com","OpenAtMicrosoft","https:\u002F\u002Fopensource.microsoft.com","https:\u002F\u002Fgithub.com\u002Fmicrosoft",[82,86,90,93,96,99,102],{"name":83,"color":84,"percentage":85},"Jupyter Notebook","#DA5B0B",100,{"name":87,"color":88,"percentage":89},"Python","#3572A5",0,{"name":91,"color":92,"percentage":89},"HTML","#e34c26",{"name":94,"color":95,"percentage":89},"Vue","#41b883",{"name":97,"color":98,"percentage":89},"JavaScript","#f1e05a",{"name":100,"color":101,"percentage":89},"Dockerfile","#384d54",{"name":103,"color":104,"percentage":89},"Shell","#89e051",46454,9507,"2026-04-07T21:25:37","MIT","Linux, macOS, Windows","未说明",{"notes":112,"python":110,"dependencies":113},"这是一个包含 12 周课程的教学大纲，而非单一的可执行软件。课程涵盖符号 AI、神经网络和深度学习等内容。支持通过 Binder 在线运行实验，无需本地配置环境。若本地运行，需自行安装 TensorFlow 或 PyTorch 框架。仓库包含 50 多种语言翻译，建议使用稀疏克隆（sparse checkout）以减少下载体积。",[114,115],"TensorFlow","PyTorch",[14,13,15,35],[118,119,120,121,122,123,124,125,126,127],"deep-learning","artificial-intelligence","machine-learning","ai","computer-vision","nlp","cnn","rnn","gan","microsoft-for-beginners","2026-03-27T02:49:30.150509","2026-04-08T12:59:06.089164",[131,136,141,146,151,156],{"id":132,"question_zh":133,"answer_zh":134,"source_url":135},24344,"如何访问课程数据或在本地运行代码时遇到 Docker、Binder、Codespaces 失败怎么办？","如果自动化工具（Docker, Binder, Codespaces）失败，建议尝试在本地计算机上手动设置环境。您可以参考官方指南 'how-to-run' 页面，使用 Conda 或 Python venv 创建虚拟环境。对于新手，可以直接在操作系统文件管理器中修改配置文件（如 requirements.txt），无需通过命令行编辑器。如果遇到特定包冲突，可能需要手动调整版本号或删除旧的虚拟环境目录后重试。","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F289",{"id":137,"question_zh":138,"answer_zh":139,"source_url":140},24345,"使用 Conda 创建虚拟环境时出现 'ResolvePackageNotFound' 或 'UnsatisfiableError' 包冲突错误如何解决？","这通常是由于 environment.yml 文件中指定的包版本过旧或与当前系统不兼容。解决方案包括：\n1. 检查 Python 安装版本。\n2. 尝试使用标准的 Python venv 代替 Conda：\n   - 创建环境：`python3 -m venv name_of_venv`\n   - 激活环境：`source name_of_venv\u002Fbin\u002Factivate` (Windows 下为 `name_of_venv\\Scripts\\activate`)\n3. 如果必须使用 Conda 且遇到依赖冲突，尝试删除已存在的同名环境目录（例如在 Windows 上位于 `C:\\Users\\\u003C用户名>\\AppData\\Local\\miniconda3\\envs\\ai4beg`），然后重新运行创建命令。","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F201",{"id":142,"question_zh":143,"answer_zh":144,"source_url":145},24346,"安装时遇到 'tokenizers' 与 'transformers' 版本冲突错误（ResolutionImpossible）怎么办？","这是因为 `requirements.txt` 中锁定的 `tokenizers` 版本（如 0.10.3）与 `transformers` 库的要求不匹配。解决方法是手动修改 `.devcontainer\u002Frequirements.txt` 文件：\n找到 `tokenizers==0.10.3` 这一行，将其更改为兼容的版本范围或具体版本。推荐改为：`tokenizers>=0.11.1,!=0.11.3,\u003C0.14` 或者直接指定一个已知可用的版本，例如 `tokenizers==0.13.3`。\n修改保存后，重新运行环境创建命令即可解决冲突。","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F237",{"id":147,"question_zh":148,"answer_zh":149,"source_url":150},24347,"Miniconda 依赖项安装持续失败如何处理？","该项目维护者已确认依赖项问题并进行了更新。如果您仍遇到 Miniconda 依赖安装失败的情况，请确保您拉取了最新的代码库版本，因为相关的依赖配置文件（如 environment.yml 或 requirements.txt）已经被修复和更新。如果问题依旧，建议清理本地缓存或尝试上述的手动调整包版本方法。","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F349",{"id":152,"question_zh":153,"answer_zh":154,"source_url":155},24348,"运行感知机（Perceptron）笔记本代码时出现数组形状不一致或绘图错误怎么办？","该问题是由于笔记本代码中的数组处理逻辑与更新后的学习材料不一致导致的。维护者已经更新了相关的 Jupyter Notebook 文件以修复此错误。请确保您从主分支（main branch）拉取了最新的代码，特别是 `lessons\u002F3-NeuralNetworks\u002F03-Perceptron\u002FPerceptron.ipynb` 文件。如果手动修复，需检查代码中添加到快照列表（snapshots）的元素形状是否一致，确保权重矩阵和准确率数值的拼接方式正确。","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAI-For-Beginners\u002Fissues\u002F233",{"id":157,"question_zh":158,"answer_zh":159,"source_url":140},24349,"作为非开发者或新手，如何在 Windows 上更简单地修改项目配置文件？","您不需要在 Miniconda 控制台或使用复杂的命令行编辑器来修改文本文件。在 Windows 11 等系统上，您可以直接使用文件资源管理器找到项目文件夹（例如 `.devcontainer` 目录下的 `requirements.txt`），右键点击文件并选择使用记事本（Notepad）或其他文本编辑器打开进行修改。保存文件后，再回到命令行终端运行安装或环境创建命令即可。这种方法降低了操作门槛，避免了命令行编辑的学习曲线。",[]]