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aishwaryanr/awesome-generative-ai-guide

A curated hub of generative AI learning courses, research paper roundups, interview prep materials, and code notebooks, organized by journey and skill level.

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What is it?

This is an awesome-style collection for people working with generative AI. It gathers courses, research paper summaries, interview preparation materials, Jupyter notebooks, and glossaries into one place. The content is organized into three journeys, Use AI, Build AI, and Understand AI, each with beginner, practitioner, and advanced levels, so readers can start from their own goal instead of scanning one long list.

Beyond the journey paths, the repository provides a topic index covering areas such as LLM foundations, prompting, retrieval and RAG, fine-tuning, AI agents, evaluation, multimodal models, and production LLMOps. It also includes role-based interview prep for AI engineers, AI product managers, forward-deployed engineers, and AI strategists, along with several free courses such as an AI evals course and an agentic AI crash course.

The project is maintained by its author and accepts pull requests for new resources, which must be placed under a journey, level, and topic.

Key features

  • 01Organizes resources into Use AI, Build AI, and Understand AI journeys with 101 to 301 levels.
  • 02Provides a topic index covering RAG, fine-tuning, agents, evaluation, and multimodal models.
  • 03Includes role-based interview prep for AI engineers, product managers, and strategists.
  • 04Lists free courses, including AI evals and agentic AI crash course materials.
  • 05Hosts Jupyter notebooks and an LLM glossary.

Use cases

  • Finding a structured starting path for learning generative AI from scratch.
  • Preparing for AI engineering or AI product manager interviews.
  • Browsing course and paper resources on a specific topic such as RAG or evaluation.
  • Locating runnable notebooks to practice LLM techniques.

Things to know

  • Some listed courses and resources have access terms set by their providers, so check each one before enrolling.
  • The Applied LLMs Mastery course is an archived 2024 edition.
  • Sponsored sections promote paid cohort courses on Maven, and the README does not endorse them.

Topics

#generative-ai#llm#awesome-list#interview-questions#learning-resources#jupyter-notebook#rag#ai-agents#awesome#large-language-models

FAQ

What is awesome-generative-ai-guide?
A curated hub of generative AI learning courses, research paper roundups, interview prep materials, and code notebooks, organized by journey and skill level. This is an awesome-style collection for people working with generative AI. It gathers courses, research paper summaries, interview preparation materials, Jupyter notebooks, and glossaries into one place. The content is organized into three journeys, Use AI, Build AI, and Understand AI, each with beginner, practitioner, and advanced levels, so readers can start from their own goal instead of scanning one long list.
Is awesome-generative-ai-guide free to use? What license does it have?
awesome-generative-ai-guide is open source under the MIT license. Check the license terms before using it in commercial products.
Is awesome-generative-ai-guide still maintained?
Actively maintained. The last commit to awesome-generative-ai-guide was on Oct 15, 2026.
What can I use awesome-generative-ai-guide for?
Finding a structured starting path for learning generative AI from scratch. Preparing for AI engineering or AI product manager interviews. Browsing course and paper resources on a specific topic such as RAG or evaluation. Locating runnable notebooks to practice LLM techniques.
Where can I get awesome-generative-ai-guide?
The source code and installation instructions are on GitHub: https://github.com/aishwaryanr/awesome-generative-ai-guide

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