{"data":{"slug":"fancyboi999-ai-engineering-from-scratch-zh","name":"ai-engineering-from-scratch-zh","tagline":"Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南","github_url":"https://github.com/fancyboi999/ai-engineering-from-scratch-zh","owner":"fancyboi999","repo":"ai-engineering-from-scratch-zh","owner_avatar_url":"https://avatars.githubusercontent.com/u/135568692?v=4","primary_language":"Python","stars":805,"forks":115,"topics":["agents","ai","ai-agents","ai-engineering","chinese","chinese-translation","computer-vision","course","deep-learning","from-scratch","generative-ai","learn-ai","llm","machine-learning","mcp","nlp","python","reinforcement-learning","transformers","tutorial"],"archived":false,"github_pushed_at":"2026-06-26T04:05:18+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/fancyboi999-ai-engineering-from-scratch-zh","markdown_url":"https://www.graphcanon.com/tools/fancyboi999-ai-engineering-from-scratch-zh.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/fancyboi999-ai-engineering-from-scratch-zh","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=fancyboi999-ai-engineering-from-scratch-zh","description":"Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南","homepage_url":"https://aieng-zh.cn","license":"MIT","open_issues":4,"watchers":7,"ai_summary":null,"readme_excerpt":"<p align=\"center\">\n  <img src=\"assets/banner.svg\" alt=\"AI Engineering from Scratch · 简体中文版\" width=\"100%\">\n</p>\n\n<p align=\"center\">\n  <b>从零开始，亲手实现每一个 AI 算法</b><br/>\n  <sub>503 节课 · 20 个阶段 · Python / TypeScript / Rust / Julia · 配套中文网站 <a href=\"https://aieng-zh.cn\">aieng-zh.cn</a></sub>\n</p>\n\n<p align=\"center\">\n  <a href=\"https://aieng-zh.cn\"><img src=\"https://img.shields.io/badge/在线阅读-aieng--zh.cn-3553ff?style=flat-square&labelColor=fafaf5\" alt=\"在线阅读 aieng-zh.cn\"></a>\n  <a href=\"ROADMAP.md\"><img src=\"https://img.shields.io/badge/lessons-503-3553ff?style=flat-square&labelColor=fafaf5\" alt=\"503 lessons\"></a>\n  <a href=\"#contents\"><img src=\"https://img.shields.io/badge/phases-20-3553ff?style=flat-square&labelColor=fafaf5\" alt=\"20 phases\"></a>\n  <a href=\"LICENSE\"><img src=\"https://img.shields.io/badge/license-MIT-1a1a1a?style=flat-square&labelColor=fafaf5\" alt=\"MIT License\"></a>\n  <a href=\"https://github.com/fancyboi999/ai-engineering-from-scratch-zh/stargazers\"><img src=\"https://img.shields.io/github/stars/fancyboi999/ai-engineering-from-scratch-zh?style=flat-square&labelColor=fafaf5&color=3553ff&cacheSeconds=21600\" alt=\"GitHub stars\"></a>\n</p>\n\n```\n░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒\n```\n\n> **84% 的学生已经在用 AI 工具，可只有 18% 觉得自己能在专业场景里用好它们。**\n> 这套课程要填的就是这道沟。\n>\n> 503 节课，20 个阶段，约 320 小时。Python、TypeScript、Rust、Julia。每节课都交付一件\n> 能复用的东西：一个提示词、一个技能、一个 agent、一个 MCP server。免费，开源，MIT。\n>\n> 你不只是学 AI，你亲手把它造出来。从头到尾，全手写。\n\n> 本项目是 [AI Engineering from Scratch](https://github.com/rohitg00/ai-engineering-from-scratch)（作者 [Rohit Ghumare](https://github.com/rohitg00)，MIT 协议）的**简体中文衍生版**。衷心感谢原作者创作并开源了这套课程。\n\n### 这个中文版做了什么\n\n不是机器翻译堆出来的镜像。在忠实翻译之上，我们做了一套面向中文读者的本地化：\n\n| | |\n|---|---|\n| 🇨🇳 **全站简体中文** | 503 节课正文、83 条术语表、测验题、`mermaid` 流程图、交互图表标签全部中文化（`agent`、`token`、`transformer` 等技术术语按惯例保留英文） |\n| 🌐 **独立中文网站 [aieng-zh.cn](https://aieng-zh.cn)** | 可搜索的课程目录、学习进度追踪、可拖动的交互式图表、命令面板（`Cmd / Ctrl + K`）、深色模式 |\n| 🎬 **配套动画讲解视频** | 3Blue1Brown 风格的无真人动画讲解，把每节课的数学推导与核心直觉做成可视化短片，中文配音、在课程页内嵌播放。Phase 1（数学基础 22 节）已上线，其余阶段陆续制作中——它是对动手推导的补充，不是替你跳过思考的速成视频 |\n| 🔍 **为 AI 检索优化** | 构建时自动生成 `sitemap.xml` / `llms.txt` / 结构化数据，方便被搜索引擎和 AI 助手引用 |\n| ✅ **课数一致性护栏** | CI 自动校验课程数（`node site/build.js --check`），防止课程列表与磁盘上的实际内容漂移 |\n\n> 翻译怎么翻见 [TRANSLATION.md](TRANSLATION.md)。课程结构、代码与上游保持一致，译文持续跟进上游更新。\n\n**目录** · [怎么运作](#怎么运作) · [课程结构](#课程的结构) · [一节课的样子](#一节课的样子) · [快速开始](#快速开始) · [每节课都有产出](#每节课都有产出) · [课程目录](#contents) · [工具箱](#工具箱) · [参与贡献](#参与贡献)\n\n## 怎么运作\n\n大多数 AI 教材都是碎片化教学。这儿一篇论文，那儿一篇微调心得，别处再来个炫酷的 agent\ndemo。这些碎片很少能拼到一起。你做出了一个聊天机器人，却讲不清它的 loss 曲线；你给\nagent 挂了个函数，却说不出调用它的那个模型内部，attention 到底在干什么。\n\n这套课程就是那根脊椎。20 个阶段，503 节课，四种语言：Python、TypeScript、Rust、Julia。\n一头是线性代数，另一头是自主 agent 集群。每个算法都先从最原始的数学手写出来。反向传播、\n分词器、注意力、agent 循环——等 PyTorch 登场时，你已经知道它底层在做什么了。\n\n每节课都跑同一个循环：读懂问题、推导数学、写代码、跑测试、留下产物。没有五分钟速成视频，\n没有复制粘贴式部署，没有手把手喂饭。免费，开源，在你自己的笔记本上就能跑。\n\n```\n░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒\n```\n\n## 课程的结构\n\n二十个阶段层层叠起来。数学是地基，agent 和生产部署是屋顶。下层的东西你已经会了，就尽管\n往前跳；但别跳过去之后，又回头纳闷上层为什么塌了。\n\n```mermaid\n%%{init: {'theme':'base','themeVariables':{'primaryColor':'#fafaf5','primaryTextColor':'#1a1a1a','primaryBorderColor':'#3553ff','lineColor':'#3553ff'}}}%%\nflowchart TB\n  P0[\"阶段 0 · 配置与工具链\"] --> P1[\"阶段 1 · 数学基础\"]\n  P1 --> P2[\"阶段 2 · 机器学习基础\"]\n  P2 --> P3[\"阶段 3 · 深度学习核心\"]\n  P3 --> P4[\"阶段 4 · 计算机视觉\"]\n  P3 --> P5[\"阶段 5 · NLP\"]\n  P3 --> P6[\"阶段 6 · 语音与音频\"]\n  P3 --> P9[\"阶段 9 · 强化学习\"]\n  P5 --> P7[\"阶段 7 · Transformer\"]\n  P7 --> P8[\"阶段 8 · 生成式 AI\"]\n  P7 --> P10[\"阶段 10 · 从零实现 LLM\"]\n  P10 --> P11[\"阶段 11 · LLM 工程\"]\n  P10 --> P12[\"阶段 12 · 多模态 AI\"]\n  P11 --> P13[\"阶段 13 · 工具与协议\"]\n  P13 --> P14[\"阶段 14 · Agent 工程\"]\n  P14 --> P15[\"阶段 15 · 自主系统\"]\n  P15 --> P16[\"阶段 16 · 多 agent 与集群\"]\n  P14 --> P17[\"阶段 17 · 基础设施与生产\"]\n  P15 --> P18[\"阶段 18 · 伦理、安全与对齐\"]\n  P16 --> P19[\"阶段 19 · 综合项目\"]\n  P17 --> P19\n  P18 --> P19\n```\n\n```\n░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒\n```\n\n## 一节课的样子\n\n每节课都待在自己的文件夹里，整套课程结构统一：\n\n```\nph","github_created_at":"2026-05-26T12:45:07+00:00","created_at":"2026-07-11T12:27:36.722033+00:00","updated_at":"2026-07-11T12:27:42.145645+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"ai-engineering","name":"ai-engineering"},{"slug":"chinese","name":"chinese"},{"slug":"agents","name":"agents"},{"slug":"ai","name":"ai"},{"slug":"course","name":"course"},{"slug":"chinese-translation","name":"chinese-translation"},{"slug":"ai-agents","name":"ai-agents"},{"slug":"computer-vision","name":"computer-vision"}],"trust":{"provenance":{"is_fork":false,"github_id":1250240320,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T12:27:37.350Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":15,"last_release_at":null},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":83,"high_count":0,"last_scan_at":"2026-07-11T12:27:39.061Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T12:27:38.695Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-11T12:27:38.695Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-11T12:27:38.695Z"}}}}