Python LlamaIndex: Step by Step RAG With Examples

Using LlamaIndex for RAG in Python

Steven Loyens
Steven Loyens 18 Lessons 1h 4m Updated intermediate ai
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Discover how to use LlamaIndex with practical examples. This framework helps you build retrieval-augmented generation (RAG) apps using Python. LlamaIndex lets you load your data and documents, create and persist searchable indexes, and query an LLM using your data as context.

In this course, you’ll learn the basics of installing the package, setting AI providers, spinning up a query engine, and running queries against remote or local models.

By the end of this course, you’ll understand that:

  • You use LlamaIndex to connect your data to LLMs, allowing you to build AI agents, workflows, query engines, and chat engines.
  • You can perform RAG with LlamaIndex to retrieve relevant context at query time, helping the LLM generate grounded answers and minimize hallucinations.

You’ll start by preparing your environment and installing LlamaIndex. From there, you’ll learn how to load your own files, build and save an index, choose different AI providers, and run targeted queries over your data through a query engine.

What’s Included:

  • 18 Lessons
  • Video Subtitles and Full Transcripts
  • 2 Downloadable Resources
  • Accompanying Text-Based Tutorial
  • Interactive Quiz to Check Your Progress
  • 2 Hands-On Coding Exercises
  • Q&A With Python Experts: Ask a Question
  • Certificate of Completion

Downloadable Resources:

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Using LlamaIndex for RAG in Python

3 Lessons 7m

  1. 1. Using LlamaIndex for RAG in Python (Overview)03:39
  2. 2. Explaining RAG02:47
  3. 3. Setting Up Your Environment01:06

Building a RAG Query Engine

11 Lessons 43m

  1. 1. Introducing the Project02:19
  2. 2. Starting the Code Example - Loading04:02
  3. 3. Coding Indexing02:33
  4. 4. Coding Querying03:05
  5. 5. Examining the Code Output03:36
  6. 6. Exercise: Build a RAG Query Pipeline08:00
  7. 7. Refactoring Code01:55
  8. 8. Persisting02:49
  9. 9. Persisting Functionality03:30
  10. 10. Testing the Output01:38
  11. 11. Exercise: Persist or Rebuild an Index10:00

Exploring Further

2 Lessons 5m

  1. 1. Looking at Next Steps03:36
  2. 2. Investigating Documents and Index02:14

Reviewing What You've Learned

2 Lessons 8m

  1. 1. Using LlamaIndex for RAG in Python (Quiz)06:30
  2. 2. Using LlamaIndex for RAG in Python (Summary)01:32
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About Steven Loyens

Steven is an Actuary, Economist and Engineer who found his passion for coding messing about with his Commodore 64 in the eighties. He loves understanding how things work and sharing that knowledge. He's an experienced coach and mentor.

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