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

📚 Table of Contents

Documentation & Learning Resources
Practical Use Cases & Projects

📖 Documentation & Learning Resources

🎯 Getting Started

GenAI Roadmap - Your complete learning path for GenAI
AI/ML Roadmap - 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 - Key terminology and concepts
LLM Fundamentals - Core concepts of Large Language Models

🧠 Core Concepts & Guides

Vector Embeddings Guide - Understanding vector representations
Prompt Engineering - Crafting effective prompts
AI Patterns - Top 25 AI design patterns
ML Reference Guide - Machine learning reference

🏗️ Architecture & Technical Stack

GenAI Tech Stacks - Technology stack overview
LLM Providers - Comparison of LLM providers
Advanced RAG Decision Flow - RAG architecture guide
GenAI Project Lifecycle - End-to-end project guide

☁️ Cloud Platform Guides

GenAI on AWS - AWS implementation | GitHub | YouTube
GenAI on Azure - Azure implementation guide
GenAI on VertexAI - 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 - Common interview questions
Agentic AI Interview Q&A - Agent-specific interview prep
90+ Multi-Agentic AI Interview Q&A - Multi-Agentic specific interview prep
AI Roles & Important Topics - Career paths and topics

🚀 Production & Enterprise

GenAI Enterprise Production Checklist - Production readiness guide

🛠️ Practical Use Cases & Projects

🔍 Retrieval-Augmented Generation (RAG)

Advanced RAG - Comprehensive RAG techniques including agentic, graph, multimodal, and 9 advanced patterns (corrective RAG, hybrid search, query expansion, etc.)
Cache-Augmented Generation - Alternative to RAG using context caching for faster responses

🤖 Agentic AI & Orchestration

Agentic AI - Multi-agent systems with CrewAI & LangGraph frameworks
AI Patterns - 25 advanced reasoning patterns (Chain-of-Thought, ReAct, Tree-of-Thought, Meta-Prompting, etc.)
MCP - Model Context Protocol - Standard protocol for LLM tool interoperability with web search
Multi-Agentic Prod Grade Content Moderation System - AI-Powered Multi-Agentic Content Moderation System with React Frontend
Handling Latency in Multi-Agentic System - How to handle Latency in Multi-Agentic System

💬 Conversational AI

Chatbot with Memory - PDF chatbot using local models with persistent conversation memory
Conversational Analytics - Full-stack app analyzing customer feedback (React + FastAPI + PostgreSQL)

🔧 LLM Providers & Tools

LLM Providers - Compare OpenAI, Gemini, Claude, Groq + local models (Ollama, HuggingFace)
Embedding Models - Guide to vector embeddings with Google, OpenAI, and HuggingFace

📊 Data & Analytics Applications

Text-to-SQL - Convert natural language to SQL queries with visualization
Graph Q&A - Query Neo4j graph databases using natural language
Sentiment Analysis - Analyze customer call transcripts for sentiment and aggressiveness
Your AI Chat Analytics - Chat analytics dashboard

🎨 Prompt Engineering & Security

Prompt Engineering - 16+ techniques from basics to APE (Automatic Prompt Engineer)
Prompt Guard - Detect prompt injections and jailbreak attempts using Meta's Llama Guard

🖼️ Multimodal & Specialized

Gemini Nano Banana - Text-to-image generation with Gemini 2.5 Flash
Llama 4 Multi-Function App - All-in-one app: chat, OCR, RAG, and agentic AI

⚡ Automation

n8n Automation - Setup and usage guide for n8n workflow automation platform

🔗 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 • AI/ML Roadmap | | Fundamentals | Essential Terms • LLM Fundamentals • Embeddings Guide | | Cloud Platforms | AWS • Azure • VertexAI | | Interview Prep | GenAI Q&A • Agentic AI Q&A | | Popular Projects | Advanced RAG • Agentic AI • Text-to-SQL |

🤝 Contributing

Contributions are welcome. To add useful resources or code:

Fork this repo

Clone it

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

Create a branch
```
git checkout -b feature-name
```
Make changes and commit
```
git commit -m "Your message"
```
Push your branch
```
git push origin feature-name
```
Open a Pull Request with a brief description of your changes.