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✨ Generative AI

Learn Generative AI —
From Basics to Production.

Structured learning paths covering LLMs, RAG systems, prompt engineering, and production deployment. Each topic is explained with real code, analogies, and hands-on exercises.

7
Learning Sections
30+
Topics
12
Projects
Quick Access
🤖 What is GenAI? New
📚 LLM Basics
⚡ Transformers
✏️ Prompt Engineering Hot
🔍 RAG Systems Hot
💬 Build a Chatbot
🗄️ Vector Databases
🔧 Fine-Tuning
🤝 Agents
Production
🚀 Deploy with FastAPI
🛡️ Evaluation
💰 Cost Optimization
🧱
1 · Foundations
Start here. Understand what GenAI is, how LLMs work, and the key concepts like tokens and embeddings — explained simply.
What is GenAI LLM Basics Tokens Embeddings
Start here →
⚙️
2 · Core Concepts
Understand transformers intuitively, how attention mechanisms work, and how to use AI APIs effectively in your applications.
Transformers Attention OpenAI API Anthropic
Explore →
⭐ Most Popular
🚀
3 · Build Your First App
Jump straight into building. Create a working chatbot, master prompt basics, and implement streaming responses. Hands-on from minute one.
Chatbot Prompts Streaming
Build now →
🏆 Flagship Track
🔍
4 · RAG Systems
The most in-demand GenAI skill right now. Learn Retrieval-Augmented Generation end-to-end — from chunking strategies to vector databases to a complete PDF Q&A project.
What is RAG Chunking Vector DB PDF Q&A Project
Master RAG →
🧠
5 · Advanced Topics
Deep dive into prompt engineering, fine-tuning your own models with LoRA, and building autonomous agents with LangChain.
Prompt Deep Dive Fine-Tuning Agents LangChain
Go deeper →
🏭
6 · Production & Scaling
Take your GenAI app from prototype to production. Evaluation frameworks, guardrails, cost optimisation, and FastAPI deployment.
Evaluation Guardrails Cost Opt. FastAPI
Ship it →
🤖
What is GenAI?
A clear, jargon-free explanation of generative AI and why it matters for engineers right now.
Learn →
📚
LLM Basics
How large language models are trained, what they predict, and why they're so powerful.
Learn →
🔢
Tokens & Embeddings
The fundamental units of LLMs — explained with simple analogies and why they matter for your costs.
Learn →
⚡
Transformers
The architecture behind every modern LLM. Understand the intuition and key steps without the maths overwhelm.
Learn →
👁️
Attention Mechanism
Why "attention is all you need" — the concept that changed everything in NLP.
Learn →
🔌
Using AI APIs
OpenAI, Anthropic, and open-source APIs. How to call them, structure messages, and handle responses.
Learn →
⭐
Most Popular Section
This is where most engineers get their first real win. Start here if you want to build something working today.
💬
Build a Chatbot
Build a fully working chatbot with conversation memory in under 50 lines of Python.
Build →
✏️
Prompt Basics
The fundamentals of writing effective prompts — system prompts, few-shot examples, and formatting.
Learn →
⚡
Streaming Responses
Make your app feel instant with streaming — stream tokens as they're generated instead of waiting.
Learn →
🏆
Flagship Track — Most In-Demand Skill
RAG is what every GenAI engineer needs right now. Master this and you'll stand out in any interview.
🔍
What is RAG?
Why LLMs hallucinate and how RAG solves it. The architecture explained clearly with a real example.
Start here →
✂️
Chunking Strategies
Fixed-size, semantic, and recursive chunking — when to use each and how it affects retrieval quality.
Learn →
🗄️
Vector Databases
Pinecone, Chroma, Weaviate — how they work and how to choose the right one for your project.
Learn →
⭐ Project
📄
PDF Q&A Project
Build a complete RAG system that can answer questions about any PDF document. End-to-end project with full code.
Build it →
✏️
Prompt Engineering
Chain-of-thought, tree-of-thought, ReAct, and advanced prompting patterns used in production.
Learn →
🔧
Fine-Tuning with LoRA
When to fine-tune vs prompt engineer. LoRA and PEFT explained — fine-tune Llama on your own data.
Learn →
🤝
Agents with LangChain
Build autonomous agents that can use tools, search the web, and complete multi-step tasks.
Learn →
🛡️
Evaluation & Guardrails
How to measure LLM quality, detect hallucinations, and implement content safety in production.
Learn →
💰
Cost Optimization
Caching, model selection, prompt compression, and batching — reduce your API costs by 70%+.
Learn →
🚀
Deploy with FastAPI
Wrap your LLM app in a production FastAPI server with async streaming, auth, and rate limiting.
Learn →
📊
Monitoring & Logging
LangSmith, Helicone, and custom logging — observability for your GenAI applications.
Learn →

Projects — Beginner to Advanced

Build real things. Each project includes full code, step-by-step instructions, and a stretch goal.

Beginner
💬 Simple Chatbot
A chatbot with memory using the OpenAI API. Under 50 lines of Python.
PythonOpenAI
Intermediate
📄 PDF Q&A System
Upload any PDF and ask questions about it using RAG. Full end-to-end project.
PythonLangChainChroma
Beginner
⚡ Streaming Chat UI
Real-time streaming responses with a clean web interface. Feels like ChatGPT.
PythonFastAPIJS
Advanced
🤝 Research Agent
An autonomous agent that can search the web, summarise papers, and write reports.
LangChainToolsMemory
Advanced
🔧 Fine-Tuned Model
Fine-tune Llama 2 on your own dataset using LoRA. Full training pipeline included.
LoRAPEFTHuggingFace
Intermediate
🏭 Production LLM API
Deploy your LLM app as a production API with auth, rate limiting, and monitoring.
FastAPIDockerRedis
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