Developing RAG Applications with LlamaIndex and Gen AI Online Course

Developing RAG Applications with LlamaIndex and Gen AI Online Course

This course introduces you to Large Language Models (LLMs) with a focus on LlamaIndex, starting with environment setup, your first program, and advanced prompt engineering. You’ll explore prompt templates, conversational prompts, semantic evaluators, embeddings, and vector databases like SQL and Chroma DB. You’ll also learn to design query pipelines—including sequential, DAG, and dataframe—for handling complex queries. In the final section, you’ll apply your skills through projects such as building a ReAct calculator agent, a document agent with dynamic tools, and a Streamlit-based code checker. By the end, you’ll be ready to develop versatile, AI-powered applications for real-world use.

Who should take this Course?

The Developing RAG Applications with LlamaIndex and Gen AI Online Course is ideal for AI developers, data scientists, and software engineers who want to build Retrieval-Augmented Generation (RAG) applications using LlamaIndex. It is also suitable for students, researchers, and technology enthusiasts looking to gain hands-on experience with generative AI and LlamaIndex to create intelligent, data-driven applications powered by large language models.

What you will learn

• Develop and implement LlamaIndex programs
• Design and utilize advanced prompt templates
• Evaluate semantic similarities effectively
• Integrate LlamaIndex with various databases
• Set up and optimize different query pipelines
• Create dynamic agents and tools for AI applications

Course Outline

Introduction

• Course Introduction
• Introduction to LLMs
• Introduction to LlamaIndex
• Introduction to Prompts
• Prompts - Advanced
• Setup your Development Environment
• Your First LlamaIndex Program

Getting Deeper into LlamaIndex

• Format Prompt Templates
• Conversational Prompts
• Semantic Similarity Evaluator
• Language Embeddings and Vector Databases
• Using a Chroma DB Vector Database
• LlamaIndex with SQL Database
• LlamaIndex Query Pipelines
• Setting up a Simple Sequential Query Pipeline
• Setting up a DAG Pipeline
• Setting up a Dataframe Pipeline
• Working with Agents and Tools
• Create a Calculator using a ReAct Agent
• Create a Document Agent with Dynamically built Tools
• Build a Code Checker with Streamlit UI