Retrieval Augmented Generation (RAG) Techniques
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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,
    and enterprise knowledge systems.

Created by Selva Prabhakaran

  • 7 Video Lessons

  • English

  • English captions

What you will learn

01

Core RAG Concepts & Workflow

02

Building a Basic RAG 

Pipeline

03

HyDE: Improving Retrieval with Hypothetical Documents

04

Advanced Chunking Strategies

05

Precision Retrieval 

with RSE

06

RAG for Structured 

Data

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

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

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 & 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 an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 75K+students

  • 50+ Courses