Retrieval Augmented Generation (RAG) Techniques

Learn how Retrieval-Augmented Generation (RAG) combines real-time data retrieval with generative AI to deliver accurate, up-to-date responses. Master the end-to-end RAG pipeline, from vector databases and embedding models to fine-tuning LLMs for context-aware generation. Get hands-on with industry tools to build powerful RAG applications for search, chatbots.

  • Master the end-to-end RAG pipeline, from vector databases and embedding models to fine-tuning LLMs for context-aware generation.
  • Get hands-on with industry tools to build powerful RAG applications for search, chatbots, and enterprise knowledge systems.

Prabhakaran SPrincipal Data Scientist

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Included in All-Access, one membership for every course.

Lessons
17
Video
3 h 6 min
Certificate
On completion

What you'll be able to do

  • Core RAG Concepts & Workflow
  • Building a Basic RAG Pipeline
  • HyDE: Improving Retrieval with Hypothetical Documents
  • Advanced Chunking Strategies
  • Precision Retrieval with RSE
  • RAG for Structured Data

Course content

1 chapter · 17 lessons · 3 h 6 min

  1. 01Retrieval Augmented Generation (RAG) Techniques17 lessons · 3 h 7 min
    1. Introduction to RAG5:22
    2. Download Resources1:00
    3. Simple RAG App19:08
    4. HyDE - Hypothetical Document Embedding16:44
    5. Simple RAG using CSV12:29
    6. Proposition Chunking11:20
    7. Relevant Segment Extraction (RSE)21:42
    8. Optimizing Chunk Sizes11:35
    9. Semantic Chunker8:53
    10. Hypothetical Prompt Embeddings9:14
    11. Explainable Retrieval8:05
    12. Corrective RAG (CRAG)11:21
    13. Hybrid Search8:52
    14. Self RAG16:23
    15. Reliable RAG7:01
    16. Document Augmentation Method8:42
    17. Multi Modal RAG9:09

What you need

  • Basics of Python
  • Foundational knowledge of Data Science
  • High school maths

Who this course is for

  • Data Science Aspirants
  • Data Science Professionals
  • Software/Data engineers interested in quantitative analysis
  • Professionals working with large datasets
  • Data analysts, economists, researchers

Your instructor

Prabhakaran S

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

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