Mastering LlamaIndex: From Fundamentals to Building AI Apps

This course teaches how to use LlamaIndex to connect with large language models, build RAG systems, extract data, and create agentic and AI applications.

Beginner

15 Lessons

Certificate of Completion

This course teaches how to use LlamaIndex to connect with large language models, build RAG systems, extract data, and create agentic and AI applications.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

23 Playgrounds

This course includes

23 Playgrounds

Course Overview

This course explores LlamaIndex’s core architecture and how it connects unstructured data to language models. You’ll learn how to connect LLMs to content sources like documents, APIs, and knowledge bases. You’ll build and refine RAG systems, extract structured data, and feed results into downstream analytics or automation workflows. Finally, you’ll orchestrate AI agents and workflows, from single-agent assistants to complex multi-agent architectures with shared memory and state. You’ll add logging, tracing...Show More

What You'll Learn

An understanding of the core architecture and use cases of LlamaIndex

Working knowledge of how to integrate any LLM with LlamaIndex for enhanced query handling

The ability to design and implement a RAG pipeline for efficient information retrieval

Proficiency in extracting structured data from unstructured text using schema-based techniques

Hands-on experience building single-agent and multi-agent systems with memory and workflow coordination

Working knowledge of monitoring, tracing, and evaluating LLM-driven applications for performance and reliability

The ability to assemble end-to-end AI solutions (e.g., Q&A systems, job application optimizers, lesson-plan generators)

What You'll Learn

An understanding of the core architecture and use cases of LlamaIndex

Course Content

Getting Started

Get an overview of the LlamaIndex course, including key topics, essential tools, and the foundational knowledge required to get started.

Introduction to the Course

Core Concepts and Using LLMs

Understand the fundamentals of LlamaIndex, how it connects with LLMs, and how to use it for AI-powered applications.

Introduction to LlamaIndex

Using LLMs with LlamaIndex

Building a RAG Pipeline

Build a retrieval-augmented generation (RAG) pipeline to enhance your AI’s ability to efficiently retrieve relevant information.

Implementing RAG with LlamaIndex

Extracting Structured Outputs from LLMs

Extract structured data from unstructured text to power AI-driven applications like document automation and knowledge retrieval.

Structured Data Extraction in LlamaIndex

Agents and Workflows

Leverage LlamaIndex to build AI agents and workflows that automate multi-step reasoning and decision-making.

Building AI Agents in LlamaIndex: Single-Agent System Building AI Agents in LlamaIndex: Multi-Agent System Enhancing Agent Capabilities with Memory in LlamaIndex Streamlining AI Pipelines with Workflows in LlamaIndex

Monitoring and Evaluating LLM Applications

2 Lessons

Learn to trace, evaluate, and improve LLM applications for greater reliability and performance.

Building Real-World Applications with LlamaIndex

3 Lessons

Build complete, real-world AI applications by combining multiple LlamaIndex concepts into cohesive, interactive systems.

Wrap Up

1 Lesson

Conclude what you’ve learned to start building smarter AI applications with LlamaIndex.

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