awesome-generative-ai-guide README

The project's README from github.com/aishwaryanr/awesome-generative-ai-guide. As one markdown file: README.md.

:star: :bookmark: awesome-generative-ai-guide

Generative AI is moving fast, and this repository is a comprehensive hub for generative AI research, courses, interview materials, notebooks, and more. Everything is now organized around one question: what do you want to do?

aishwaryanr%2Fawesome-generative-ai-guide | Trendshift aishwaryanr%2Fawesome-generative-ai-guide | Trendshift

What do you want to do?

Pick the door that fits you. Each journey has its own 101 to 301 path.

Journey and level grid

Pick your row (who you are) and your column (how far you want to go), then click in. Levels mean something different in each journey: depth is relative to that journey's goal.

Journey 101 Start 🟢 201 Practitioner 🟡 301 Advanced 🔴
🧑‍💻 Use AI what LLMs are; prompting basics; chat tools well power-prompting; projects; connecting tools; agent harnesses at work personal automation; multi-step agent workflows for yourself
🏗️ Build AI how LLMs work enough to build; the app stack; your first LLM app RAG, agents, evaluation, fine-tuning, guardrails LLMOps, production scale, advanced agents and RAG, security, system design
🔬 Understand AI transformers; key papers; how to read a paper active research areas: reasoning, agents, RAG, evaluation the frontier: monthly papers, research tables, State of AI

Build is the flagship journey and the deepest one. The 90+ free courses and code notebooks that used to be one long list are now sorted into these cells by level and tagged by topic.

Browse by Topic

Already know your subject? Jump straight to it. Each topic page gathers everything on that subject and shows which journey and level each piece serves.

LLM Foundations · Prompting and Context · Retrieval and RAG · Fine-tuning · AI Agents · Evaluation and Observability · Multimodal · Production and LLMOps · Safety and Security

Or see every free course in one place: All free courses, by topic.

Free, created by Aishwarya Naresh Reganti and the LevelUp Labs team, several with certification:

For every free course (LevelUp Labs originals and vetted external), organized by topic, see the full All Free Courses, by Topic list.

Want to learn live with us? The courses above are free. We also teach cohort-based courses on Maven, and more than 3,000 builders have learned with us so far: AI System Design (design real generative-AI systems end to end, the Problem-First way) and Advanced AI Evals (the evaluation and improvement loops behind reliable LLM and agent products). See all our live courses.

:star: Top AI Tools List

Discover our favorite AI tools spanning every layer of AI application development. See Our Favourite AI Tools.

:computer: Interview Prep

A full Role-Based Interview Prep hub: pick your role and work its folder end to end (overview, interview rounds, a deep question bank with answers, resources, courses, and a prep plan).

Everyone starts with the shared 60 GenAI Interview Questions, then works their role. System-design interview drills are planned for a later build phase.

:speaker: What's new

Newest first:

:paperclip: Resources

:black_nib: Contributing

If you want to add to the repository or find any issues, please feel free to raise a PR. Place your addition in the right journey, level, and topic using the journey and level grid and the browse by topic index as your guide.

:pushpin: Cite Us

To cite this guide, use the format below:

@article{areganti_generative_ai_guide,
author = {Reganti, Aishwarya Naresh},
journal = {https://github.com/aishwaryanr/awesome-generative-ai-guide},
month = {01},
title = {{Generative AI Guide}},
year = {2026}
}

License

MIT License

** Sponsored sections, where present, are marked. We do not endorse or guarantee the product or service and are not responsible for any issues arising from its use. Please evaluate and use at your discretion.

awesome-generative-ai-guide (aishwaryanr/awesome-generative-ai-guide)

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29.9K ·GitHub
Awesome-generative-ai-guide
这是什么?一个生成式 AI 学习的一站式 GitHub 资源库:包含研究动态、90 多门免费课程、代码笔记本和面试准备资料,全部围绕一个问题组织——你想用 AI 做什么?
这是一门我要跟着学的课程,还是一堆链接的合集?它是一份精选指南,而不是单一课程:90 多门免费课程和代码笔记本按“旅程 + 等级”划分成格子,并按主题打上标签,旁边还有维护者自己的特色课程。
所有内容真的都免费吗,还是有什么坑?特色课程是免费的,其中好几门还提供认证证书,但这个团队也销售基于班级的 Maven 付费课程,仓库里的赞助部分也有明确标注。
它是面向完全的初学者,还是已经在做 AI 的人?两者都是——这个表格从 101 级(了解什么是 LLM、提示词基础)一直排到 301 级(LLMOps、每月前沿论文),深度取决于每条旅程的目标。
我可以把这些内容用于自己的学习或教学吗?可以——该仓库采用 MIT 许可证,内容可以自由复用和修改。
维护者自己提供了哪些免费课程?五门 LevelUp Labs 特色课程:AI Evals for Everyone(含认证,共 10 章,讲如何评估 LLM 和智能体系统)、OpenClaw Mastery(含认证,用 10 天打造个人 AI 助手)、Agentic AI Crash Course(共 10 部分,涵盖智能体、RAG、MCP、记忆)、Generative AI Genius,以及已归档的 11 周 Applied LLMs Mastery(2024 版)。
除了课程和面试准备,里面还有什么?ICLR 2024 论文摘要、一份共 6 部分的 LLM Lingo 常见术语表、每月最佳 GenAI 论文清单、一份 State of AI 2025 报告,以及一份覆盖 AI 应用开发各层的 Top AI Tools 工具清单。
为什么现在所有内容都按旅程分类?原先冗长的单一课程列表被重新围绕目标组织——使用 AI、构建 AI、理解 AI,或准备面试——其中 Build(构建)是旗舰级的、内容最深的旅程。
What are similar projects?ai-system-design, awesome-ai-engineering, Prompt-Engineering-Guide, Agent-Learning-Hub, LLMsPracticalGuide, llm_interview_note, ai-engineering-interview-questions-company-wise, awesome-chatgpt-zh
Which topics is it in?jupyter-notebook, llms, papers, interview-questions, interview-preparation, course, evaluation, large-language-models, prompt-engineering, awesome, rag, generative-ai
Creator
aishwaryanr
Size
183.5 MB
Stars
29.9K
Updated
CommitOct 15
Age
2y
Commits · 90 Days