A one stop repository for generative AI research updates, interview resources, notebooks and much more!
: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?
What do you want to do?
Pick the door that fits you. Each journey has its own 101 to 301 path.
- 🧑💻 I want to use AI in my work → Use AI
- 🏗️ I want to build AI systems → Build AI
- 🔬 I want to understand the research → Understand AI
- 💬 I'm prepping for an interview → Interview Prep hub
- 📚 I just want to browse every free course → All free courses, by topic
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.
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.
:mortar_board: Featured LevelUp Labs courses
Free, created by Aishwarya Naresh Reganti and the LevelUp Labs team, several with certification:
- AI Evals for Everyone (certified): 10 chapters on evaluating LLM and agentic systems.
- OpenClaw Mastery for Everyone (certified): a 10-day path to configure and run your own personal AI assistant.
- Agentic AI Crash Course: 10 parts on agents, tools, RAG, MCP, planning, memory, and multi-agent systems.
- Generative AI Genius: a no-math beginner introduction to generative AI.
- Applied LLMs Mastery (2024 edition): an 11-week foundational course, archived as a 2024 edition. Course website.
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).
- 🏗️ AI Engineer: build LLM apps, RAG, agents, evaluation, and system design.
- 📋 AI Product Manager: product sense, metrics, tradeoffs, and responsible AI.
- 🚀 Forward-Deployed Engineer: build, integrate, and deploy at the customer under ambiguity.
- 🧭 AI Strategist: strategy, ROI, build vs buy, governance, and change management.
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:
- OpenClaw Mastery for Everyone is live with certification. (Course)
- AI Evals for Everyone is live with certification. (Course)
- State of AI 2025 Report published, with its own build pipeline. (Report)
- Agentic AI Crash Course released in 10 parts. (Course)
- Living research tables for evaluation, agentic search and retrieval, and RAG are being kept current. (Research updates)
:paperclip: Resources
- ICLR 2024 Paper Summaries
- LLM Lingo: a 6-part glossary of common LLM terms.
- Monthly Best GenAI Papers: the monthly paper lists (see Understand AI).
: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
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