Generative Ai

         

🎯 Learn AI/ML Interactively

I built AI-ML Companion - every AI, ML, GenAI and Agentic AI concept covered here, taught visually with animated diagrams, quizzes, and hands-on Python.

260+ modules • 20 tracks • 9 real-world projects • 11 tracks free to start

[](https://aimlcompanion.ai)

Your go-to hub for end-to-end GenAI learning. ⭐ Star this repo to stay updated with the latest GenAI resources :)

📚 Table of Contents

• [Documentation & Learning Resources](#-documentation--learning-resources)
• [Practical Use Cases & Projects](#-practical-use-cases--projects)

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📖 Documentation & Learning Resources

🎯 Getting Started

• [GenAI Roadmap](./GenAI_Roadmap.md) - Your complete learning path for GenAI
• [AI/ML Roadmap](./docs/aimlroadmap.pdf) - Comprehensive AI/ML learning guide
• AI-ML Companion - Interactive AI/ML learning platform with 17 tracks, 250+ modules, visualizations, quizzes, and hands-on coding (ML fundamentals → LLMs → 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

🧠 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

🏗️ 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

☁️ 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

💼 Career & Interview Preparation

• AI Scenario based Interview Q&A - ML/GenAI/Agentic AI Scenario based Interview Q&A
• [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

🚀 Production & Enterprise

• [GenAI Enterprise Production Checklist](./docs/genaienterpriseprodchecklist.pdf) - Production readiness guide

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🛠️ Practical Use Cases & Projects

🔍 Retrieval-Augmented Generation (RAG)

• [Advanced RAG](./genai-usecases/advance-rag/) - Comprehensive RAG techniques including agentic, graph, multimodal, and 9 advanced patterns (corrective RAG, hybrid search, query expansion, etc.)
• [Cache-Augmented Generation](./genai-usecases/cacheaugmentedgeneration/) - Alternative to RAG using context caching for faster responses

🤖 Agentic AI & Orchestration

• [Agentic AI](./genai-usecases/agentic-ai/) - Multi-agent systems with CrewAI & LangGraph frameworks
• [AI Patterns](./genai-usecases/ai-patterns/) - 25 advanced reasoning patterns (Chain-of-Thought, ReAct, Tree-of-Thought, Meta-Prompting, etc.)
• [MCP - Model Context Protocol](./genai-usecases/mcp/) - Standard protocol for LLM tool interoperability with web search
• [Multi-Agentic Prod Grade Content Moderation System](./genai-usecases/content-moderation-system/) - AI-Powered Multi-Agentic Content Moderation System with React Frontend
• [Handling Latency in Multi-Agentic System](./docs/handling-latency-in-multi-agentic-systems.pdf) - How to handle Latency in Multi-Agentic System

💬 Conversational AI

• [Chatbot with Memory](./genai-usecases/chatbot-with-memory/) - PDF chatbot using local models with persistent conversation memory
• [Conversational Analytics](./genai-usecases/conversational-analytics/) - Full-stack app analyzing customer feedback (React + FastAPI + PostgreSQL)

🔧 LLM Providers & Tools

• [LLM Providers](./genai-usecases/llm-providers/) - Compare OpenAI, Gemini, Claude, Groq + local models (Ollama, HuggingFace)
• [Embedding Models](./genai-usecases/embedding-models/) - Guide to vector embeddings with Google, OpenAI, and HuggingFace

📊 Data & Analytics Applications

• [Text-to-SQL](./genai-usecases/text-to-sql/) - Convert natural language to SQL queries with visualization
• [Graph Q&A](./genai-usecases/graph-qa/) - Query Neo4j graph databases using natural language
• [Sentiment Analysis](./genai-usecases/sentiment-analysis/) - Analyze customer call transcripts for sentiment and aggressiveness
• [Your AI Chat Analytics](./genai-usecases/youraichat_analytics/) - Chat analytics dashboard

🎨 Prompt Engineering & Security

• [Prompt Engineering](./genai-usecases/prompt-engineering/) - 16+ techniques from basics to APE (Automatic Prompt Engineer)
• [Prompt Guard](./genai-usecases/prompt-guard/) - Detect prompt injections and jailbreak attempts using Meta's Llama Guard

🖼️ Multimodal & Specialized

• [Gemini Nano Banana](./genai-usecases/gemini-nano-banana/) - Text-to-image generation with Gemini 2.5 Flash
• [Llama 4 Multi-Function App](./genai-usecases/llama-4-multi-function-app/) - All-in-one app: chat, OCR, RAG, and agentic AI

⚡ Automation

• [n8n Automation](./genai-usecases/n8n-automation/) - Setup and usage guide for n8n workflow automation platform

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🔗 Quick Access Links

| Category | Resources | |----------|-----------| | Learning Platform | AI-ML Companion — Interactive AI/ML learning with 17 tracks, 250+ modules, quizzes & coding | | Learning Path | [GenAI Roadmap](./GenAIRoadmap.md) • [AI/ML Roadmap](./docs/aimlroadmap.pdf) | | Fundamentals | [Essential Terms](./docs/essential-terms-genai.pdf) • [LLM Fundamentals](./docs/llm_fundamentals.pdf) • [Embeddings Guide](./docs/vector-embeddings-guide.pdf) | | Cloud Platforms | [AWS](./docs/genai-with-aws-cloud.pdf) • [Azure](./docs/genai-with-azure-cloud.pdf) • [VertexAI](./docs/genai-with-vertexai.pdf) | | Interview Prep | [GenAI Q&A](./docs/genai-interview-questions.pdf) • [Agentic AI Q&A](./docs/agentic-ai-interview-questions.pdf) | | Popular Projects | [Advanced RAG](./genai-usecases/advance-rag/) • [Agentic AI](./genai-usecases/agentic-ai/) • [Text-to-SQL](./genai-usecases/text-to-sql/) |

🤝 Contributing

Contributions are welcome. To add useful resources or code:

1. Fork this repo

1. Clone it

`` git clone https://github.com/genieincodebottle/generative-ai.git ``

1. Create a branch

`` git checkout -b feature-name ``

1. Make changes and commit

`` git commit -m "Your message" ``

1. Push your branch

`` git push origin feature-name ``

1. Open a Pull Request with a brief description of your changes.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: genieincodebottle
• Source: genieincodebottle/generative-ai
• License: MIT
• Homepage: https://aimlcompanion.ai/

Install and usage instructions live in the source repository linked above.