RAG and Agents Bootcamp
Step up into Generative AI by learning RAG and Agents
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About this course
Contributors & Instructors
What you will learn?
Course Content
1. Module-1
5
2
What are RAG and Agents?
How does RAG work?
How is RAG different from fine-tuning?
How do Agents work?
Session: Introduction to RAG and Agents
Quiz
Quiz
2. Module-2
8
Chunking and why is it important
Embeddings
Vector databases
LlamaIndex
Notebook: Chat with our own data
Session: Building RAG pipelines using LlamaIndex
Notebook: ChromaDB Vector Store using LlamaIndex
Notebook
3. Module-3
9
Langchain
Notebook:Conversational RAG
Session:Advanced RAG using Langchain
Re-ranking
Hybrid Search
Notebook: Simple RAG using Langchain
Notebook: Hybrid Search
Notebook: Re-reanking
Session: Build RAG pipelines using Langchain
4. Module-4
6
Overview and Getting Started with BeyondLLM
Understanding Core Components
Evaluation of RAG pipeline
Notebook: Evaluate RAG Pipeline
Notebook: Advanced RAG BeyondLLM
Session: Evaluate RAG using BeyondLLM
5. Module 5
4
Introduction to GenAI stack
Understanding the Core Concepts
Notebook: Chat with PDF No code tool
Session:Building LLM Apps with no code tools
6. Module 6
6
Introduction to Agents
Introduction & Overview of Various Agent Frameworks
Notebook: CrewAI
Notebook: AutoGen
Notebook:Nested Chats for Tool Use in Conversational Chess
Session:Building Agentic Workflows using AutoGen
7. Module-7
6
Introduction and Getting Started with OpenAGI
Core Concepts in OpenAGI
Notebook: Open Source Single Agent Execution
Notebook: Build Agentic Workflow using OpenAGI
Notebook: Building Agents using OpenAGI
Session: Build Agentic Workflows using OpenAGI
8. Module- 8
9
Introduction
Zero-Shot Prompting
One-Shot Prompting
Few-Shot Prompting
One-Shot vs. Few-Shot Prompting
Chain-of-Thought Prompting
Tree of Thoughts
ReAct Prompting
Reflexion
9. Final Assignment
1
Submit Notebook
