GEN AI COURSE CONTENT
1. Foundation & Tools
- What is Generative AI?
- Evolution from ML to Neural Networks
- Overview of LLMs & Transformers
- Popular Models: GPT-3/4, PaLM, BERT
- LangChain & HuggingFace Intro
- Prompt Engineering Basics
2. Embeddings & Vector Databases
- Word Embeddings & Vectorization
- Vector Databases: Pinecone, ChromaDB
- Semantic Search Concepts
- Split & Merge Text Chunks
- Text Embeddings using OpenAI / HF
3. Retrieval Augmented Generation (RAG)
- Intro to RAG Pipelines
- Document Retrieval Strategies
- Using Retrieval QA Chains
- LangChain Document Loaders
- Chunk optimization & indexing
- RAG pipelines with Vector Stores
4. Application with OpenAI & LangChain
- LLM API Integration (OpenAI, Claude)
- Building a Chat UI
- Simple Sequential Chains
- Conversational Memory & Cost Control
- Tool design vs GPT Interface: Tradeoffs
5. Project Work
- Vector Embedding + LangChain Project
- Restaurant App with Name + Menu Generator
- Equity Research Automation
- Semantic Search QA with Document Sources
- RAG Pipeline Assembly & Demo
- SQL + Generative QA Integration
6. Career & Certification
- Capstone GEN AI Project
- Project Submission & Review
- Interview Questions & LLM Use Cases
- Certificate of Completion
