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Generative Ai
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, intervi
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π― Learn AI/ML Interactively
I built [AI-ML Companion](https://aimlcompanion.ai) - every AI, ML, GenAI and Agentic AI concept covered here, taught visually with animated diagrams, quizzes, and hands-on Python.
260+ modules β’ 20 tracks β’ 9 real-world projects β’ 11 tracks free to start
[](https://aimlcompanion.ai)
Your go-to hub for end-to-end GenAI learning. β Star this repo to stay updated with the latest GenAI resources :)
π Table of Contents
π Documentation & Learning Resources
π― Getting Started
- [GenAI Roadmap](./GenAI_Roadmap.md) - Your complete learning path for GenAI
- [AI/ML Roadmap](./docs/ai_ml_roadmap.pdf) - Comprehensive AI/ML learning guide
- [AI-ML Companion](https://aimlcompanion.ai/) - Interactive AI/ML learning platform with 17 tracks, 250+ modules, visualizations, quizzes, and hands-on coding (ML fundamentals β LLMs β MLOps)
- [Essential GenAI Terms](./docs/essential-terms-genai.pdf) - Key terminology and concepts
- [LLM Fundamentals](./docs/llm_fundamentals.pdf) - Core concepts of Large Language Models
π§ Core Concepts & Guides
- [Vector Embeddings Guide](./docs/vector-embeddings-guide.pdf) - Understanding vector representations
- [Prompt Engineering](./docs/prompt_engineering.ipynb) - Crafting effective prompts
- [AI Patterns](./docs/ai-patterns.pdf) - Top 25 AI design patterns
- [ML Reference Guide](./docs/ml-reference-guide.pdf) - Machine learning reference
ποΈ Architecture & Technical Stack
- [GenAI Tech Stacks](./docs/genai-tech-stacks.pdf) - Technology stack overview
- [LLM Providers](./docs/llm_providers.pdf) - Comparison of LLM providers
- [Advanced RAG Decision Flow](./docs/advance-rag-decision-flow-chart.pdf) - RAG architecture guide
- [GenAI Project Lifecycle](./docs/genai-project-lifecycle.pdf) - End-to-end project guide
βοΈ Cloud Platform Guides
- [GenAI on AWS](./docs/genai-with-aws-cloud.pdf) - AWS implementation | GitHub | YouTube
- [GenAI on Azure](./docs/genai-with-azure-cloud.pdf) - Azure implementation guide
- [GenAI on VertexAI](./docs/genai-with-vertexai.pdf) - Google Cloud Vertex AI guide
πΌ Career & Interview Preparation
- [GenAI Interview Q&A](./docs/genai-interview-questions.pdf) - Common interview questions
- [Agentic AI Interview Q&A](./docs/agentic-ai-interview-questions.pdf) - Agent-specific interview prep
- [90+ Multi-Agentic AI Interview Q&A](./docs/multi-agentic-interview-qna-latest.pdf) - Multi-Agentic specific interview prep
- [AI Roles & Important Topics](./docs/ai-roles-important-topics.pdf) - Career paths and topics
Don't lose this
Three weeks from now, you'll want Generative Ai again. Will you remember where to find it?
Save it to your library and the next time you need Generative Ai, itβs one tap away β from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
β‘ Pro tip for geeks: add a-gnt π€΅π»ββοΈ as a custom connector in Claude or a custom GPT in ChatGPT β one click and your library is right there in the chat. Or, if youβre in an editor, install the a-gnt MCP server and say βuse my [bench name]β in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, intervi. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog β worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
Read more:
What's New
Imported from GitHub
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