AI engineering education (LLMs/RAG/agents)
A hub of tutorials and hands-on projects for learning LLMs, RAG, and AI agents.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose for a structured 21-lesson course with slide decks and code, if you prefer guided learning over a project collection.
21 Lessons, Get Started Building with Generative AI
Choose for a continuous from-scratch build-based tutorial series instead of a multi-project hub.
Learn it. Build it. Ship it for others.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose for a Chinese-language resource guide with news, prompts, and tool tutorials for broader coverage.
程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Prompt 提示词大全、AI 知识百科（Agent Skills / RAG / MCP / A2A）、AI 编程教程（Harness Engineering）、AI 工具用法（Cursor / Claude Code / TRAE / Codex / Copilot）、AI 开发框架教程（Spring AI / LangChain）、AI 产品变现指南，帮你快速掌握 AI 技术，走在时代前沿。本项目为开源文档 aiguide，已升级为鱼皮 AI 导航网站
Choose for a focused reference on prompt/context engineering with papers and notebooks, if you need a knowledge base rather than projects.
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Choose for a structured MLOps curriculum covering data/training/deployment, if your focus is production ML rather than LLM apps.
Learn how to develop, deploy and iterate on production-grade ML applications.
Choose for a broad 12-week beginner AI course covering classical ML and deep learning, if you are a true beginner wanting a guided curriculum.
12 Weeks, 24 Lessons, AI for All!
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
An older MLOps course (last push 2y ago); choose only for classic ML production practices.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Choose for a narrow deep-dive into implementing reasoning LLMs in PyTorch.
Implement a reasoning LLM in PyTorch from scratch, step by step
An outdated ML study plan (2018); useful only for classical ML background.
A complete daily plan for studying to become a machine learning engineer.
Choose for a Chinese-language hands-on tutorial on building LLMs from scratch; narrower coverage of model internals.
📚 从零开始构建大模型
Choose for Chinese-language LLM interview questions and notes, if you're preparing for AI engineer interviews.
主要记录大语言大模型（LLMs） 算法（应用）工程师相关的知识及面试题
These projects were analysed and named ai-engineering-hub among their alternatives. The relationship is not symmetric — how ai-engineering-hub rates them is a separate judgement, made when ai-engineering-hub is analysed in its own right.
calls ai-engineering-hub “Use instead of the seed for more in-depth, current LLM/RAG/agent tutorials.”
21 Lessons, Get Started Building with Generative AI
calls ai-engineering-hub “When you want in-depth tutorials on LLMs, RAGs, and AI agents with practical notebooks.”
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
calls ai-engineering-hub “Choose this for an equally broad collection of LLM/RAG/agent tutorials with MIT license.”
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
calls ai-engineering-hub “When you want an actively maintained, MIT-licensed tutorial hub covering LLMs, RAG, and agent applications.”
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
calls ai-engineering-hub “Choose this if you want a broader, actively updated AI engineering tutorial hub covering RAG alongside LLM and agent topics.”
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
calls ai-engineering-hub “For hands-on LLM/RAG/agent application tutorials rather than large-model training/inference ops.”
Machine Learning Engineering Open Book
calls ai-engineering-hub “Choose it when you prefer free, hands-on tutorials over a book-centric companion.”
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
calls ai-engineering-hub “Choose for project-first LLM/RAG/agent tutorials; it offers a hands-on alternative to the seed's interview-paper style.”
每个人都能看懂的大模型知识分享，LLMs春/秋招大模型面试前必看，让你和面试官侃侃而谈
calls ai-engineering-hub “choose for hands-on tutorials on LLMs/RAG/agents rather than a structured course.”
Learn it. Build it. Ship it for others.
calls ai-engineering-hub “when you want hands-on tutorials for LLMs, RAG, and agents rather than general DL notes.”
✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
calls ai-engineering-hub “Hands-on LLM/RAG/agent tutorials when your focus is only on building AI applications, not the broader AI ecosystem.”
程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Prompt 提示词大全、AI 知识百科（Agent Skills / RAG / MCP / A2A）、AI 编程教程（Harness Engineering）、AI 工具用法（Cursor / Claude Code / TRAE / Codex / Copilot）、AI 开发框架教程（Spring AI / LangChain）、AI 产品变现指南，帮你快速掌握 AI 技术，走在时代前沿。本项目为开源文档 aiguide，已升级为鱼皮 AI 导航网站