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RAG: Beyond Basics

2h 40m 48s
English
Paid

Explore the cutting-edge world of Retrieval-Augmented Generation (RAG) in this comprehensive course designed to deepen your understanding of both the practical and theoretical aspects of RAG. You will master not only the techniques but also the underlying principles that make these methods effective. Additionally, you will gain the skills to develop dependable "chat with documents" applications, leveraging the latest advancements in Large Language Models (LLMs) and advanced RAG methodologies.

Course Overview

This program progresses from building a basic pipeline to delving into advanced strategies like re-ranking and query expansion. You will also learn to work with a variety of models, including commercial and local ones. The curriculum effectively blends theoretical knowledge with hands-on programming experience using Python. You will become adept at utilizing tools such as LangChain and Streamlit, which are pivotal in the RAG landscape.

Who Should Enroll?

The course is tailored for developers, SaaS product founders, and managers who are eager to swiftly harness the potential of large volumes of textual data. By the course's conclusion, participants will not only have constructed their own fully functioning RAG pipeline but also gained a profound comprehension of strategies necessary to elevate application performance significantly.

What You Will Learn

  • Understand the core principles and workings of Retrieval-Augmented Generation (RAG).
  • Develop "chat with documents" applications using state-of-the-art LLMs.
  • Build and enhance a RAG pipeline with hands-on Python programming.
  • Apply advanced techniques, such as re-ranking and query expansion.
  • Utilize essential tools like LangChain and Streamlit for RAG applications.

About the Author: Prompt Engineering

Prompt Engineering thumbnail

Prompt Engineering is the YouTube channel and paid-course brand of an AI engineer focused on practical RAG (Retrieval-Augmented Generation) implementations and the broader applied LLM toolchain.

The CourseFlix listing carries RAG — Beyond Basics — a deep treatment of production RAG systems covering chunking strategies, embedding choice, vector-store selection, reranking, and the eval craft that separates working RAG from RAG that hallucinates.

Material is paid and aimed at engineers building production RAG pipelines on top of LLM APIs and vector databases. For the broader RAG / AI App Building track on CourseFlix, see the RAG category page.

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#1: What is RAG? Why we NEED it?
All Course Lessons (27)
#Lesson TitleDurationAccess
1
What is RAG? Why we NEED it? Demo
04:59
2
Setting up Virtual Environment
04:04
3
Setting Up API Keys
03:52
4
Deep Dive into RAG Pipeline Structure
04:01
5
Demystifying Embedding Models and Vector Storage
06:18
6
Google Colab Setup
03:10
7
End-to-End RAG Pipeline - Code Time
02:11
8
Loading and Processing PDF Files
02:36
9
How Chunking Works
06:49
10
Focus on Parsing than Chunking
02:07
11
Chunk Size as Function of Text Embedding Models
05:28
12
The Retrieval in RAG
04:38
13
Putting Everything Together - 1st Iteration of RAG
05:13
14
RAG: Advanced Techniques
01:13
15
Improving RAG with Re-ranking for Precise Information Retrieval - Part 1
06:41
16
Re-Ranking with GPT-4, ColBERT, and Cohere
07:32
17
Improving Information Retrieval with Query Expansion using LLMs
08:14
18
Enhancing Search with Hypothetical Documents Embedding Technique
08:02
19
Enhancing Document Retrieval with Ensemble Techniques
06:55
20
Hierarchical Chunking - Exploring the Parent Document Retriever
08:25
21
From Notebook to working Scripts
12:05
22
Creating Streamlit UI App
05:02
23
Private and local Chat with PDFs
04:43
24
The Recap
03:58
25
Contextual Retrieval - Adding Context to Your Chunks
09:31
26
Contextual Retrieval - Implementation
09:26
27
Multimodal RAG - Working with Images and Tables
13:35
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Course content

27 lessons · 2h 40m 48s
Show all 27 lessons
  1. 1 What is RAG? Why we NEED it? 04:59
  2. 2 Setting up Virtual Environment 04:04
  3. 3 Setting Up API Keys 03:52
  4. 4 Deep Dive into RAG Pipeline Structure 04:01
  5. 5 Demystifying Embedding Models and Vector Storage 06:18
  6. 6 Google Colab Setup 03:10
  7. 7 End-to-End RAG Pipeline - Code Time 02:11
  8. 8 Loading and Processing PDF Files 02:36
  9. 9 How Chunking Works 06:49
  10. 10 Focus on Parsing than Chunking 02:07
  11. 11 Chunk Size as Function of Text Embedding Models 05:28
  12. 12 The Retrieval in RAG 04:38
  13. 13 Putting Everything Together - 1st Iteration of RAG 05:13
  14. 14 RAG: Advanced Techniques 01:13
  15. 15 Improving RAG with Re-ranking for Precise Information Retrieval - Part 1 06:41
  16. 16 Re-Ranking with GPT-4, ColBERT, and Cohere 07:32
  17. 17 Improving Information Retrieval with Query Expansion using LLMs 08:14
  18. 18 Enhancing Search with Hypothetical Documents Embedding Technique 08:02
  19. 19 Enhancing Document Retrieval with Ensemble Techniques 06:55
  20. 20 Hierarchical Chunking - Exploring the Parent Document Retriever 08:25
  21. 21 From Notebook to working Scripts 12:05
  22. 22 Creating Streamlit UI App 05:02
  23. 23 Private and local Chat with PDFs 04:43
  24. 24 The Recap 03:58
  25. 25 Contextual Retrieval - Adding Context to Your Chunks 09:31
  26. 26 Contextual Retrieval - Implementation 09:26
  27. 27 Multimodal RAG - Working with Images and Tables 13:35

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Frequently asked questions

What is RAG: Beyond Basics about?
Explore the cutting-edge world of Retrieval-Augmented Generation (RAG) in this comprehensive course designed to deepen your understanding of both the practical and theoretical aspects of RAG. You will master not only the techniques but…
Who teaches RAG: Beyond Basics?
RAG: Beyond Basics is taught by Prompt Engineering. You can find more courses by this instructor on the corresponding source page.
How long is RAG: Beyond Basics?
RAG: Beyond Basics contains 27 lessons with a total runtime of 2 hours 40 minutes. All lessons are available to watch online at your own pace.
Is RAG: Beyond Basics free to watch?
RAG: Beyond Basics is part of CourseFlix's premium catalog. A CourseFlix subscription unlocks the full video player; the course description, table of contents, and preview information are available to everyone.
Where can I watch RAG: Beyond Basics online?
RAG: Beyond Basics is available to watch online on CourseFlix at https://courseflix.net/course/rag-beyond-basics. The page hosts every lesson with the integrated video player; no download is required.