Gen AI Workshop | Advanced RAG Techniques
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Introduction to Advanced RAG: Enhance Your Retrieval-Augmented Generation
Workshop Overview:
Join Satyajeet Narayan for an immersive 1-hour session exploring Advanced Retrieval-Augmented Generation techniques to enhance your Retrieval-Augmented Generation.
This workshop is designed for anyone exploring the world of AI and advanced chatbot development—whether you're a beginner, a tech enthusiast, or a professional expanding your skill set. If you're curious about how AI-powered chatbots, particularly those leveraging Retrieval-Augmented Generation (RAG), are built, this session is for you. Basic Python knowledge (like writing a simple "Hello World" program) is helpful. With curiosity and enthusiasm, you'll gain a strong foundation in RAG principles and walk away with practical knowledge, working code, and a deeper understanding of how AI can transform chatbots. No prior AI experience is necessary—we'll guide you step-by-step!
Key Learning Objectives
- Master the fundamentals of advanced RAG architectures
- Gain hands-on experience building powerful information retrieval system
- Learn to choose the appropriate type of Retrieval-Augmented Generation (RAG) based on specific scenarios and use cases.
- Develop practical skills in chatbot development.
Schedule Breakdown
Part 1: Basic overall understanding of the RAG architecture (4:00 PM - 4:10 PM)
- Introduction to RAG architecture
- Code to create a basic RAG
- Benefits and drawbacks of basic RAG and scenarios where RAG can be helpful
Part 2: Advanced RAG 1: Hybrid Search (4:10 - 4:25 PM)
- Introduction to the Hybrid Search architecture
- Code to create a Hybrid Search with Ensemble Retriever
- Benefits and drawbacks of Hybrid Search and scenarios where Hybrid Search can be helpful
Part 3: Advanced RAG 2: Parent Document Retriever (4:25 - 4:35 PM)
- Introduction to the Parent Document Retriever architecture
- Code to create different types of Parent Document Retrievers
- Benefits and drawbacks of Parent Document Retrievers and scenarios where Parent Document Retrievers can be helpful.
Part 4: Advanced RAG 2: RAG Fusion (4:35 - 4:45 PM)
- Introduction to the RAG Fusion architecture
- Code to create RAG Fusion
- Benefits and drawbacks of RAG Fusion and scenarios where RAG Fusion can be helpful.
Part 5: Interactive Learning (4:45 - 5:00 PM)
- Open Q&A session
- Project showcase
Technical Requirements
- Working knowledge of Python
- Laptop with minimum 4GB RAM