Building GraphRAG from Scratch
logo
Blogs Pricing The Course Resources Store Login
Contact us

Building GraphRAG From Scratch:
A Hands-On Walkthrough

  • Build a complete GraphRAG pipeline step by step — from document chunking and entity-relation extraction to
    creating a Neo4j knowledge graph.
  • Learn why vanilla RAG struggles with complex, multi-hop questions and how GraphRAG improves retrieval using
    knowledge graphs.
  • Compare no-retrieval, vanilla RAG, and GraphRAG outputs to understand where graph-based retrieval adds value.

Created by Selva Prabhakaran

  • 10 Video Lessons

  • English

What you will learn

01

How GraphRAG improves retrieval

02

Why vanilla RAG falls 

short

03

Document chunking 

for RAG

04

Entity and relation 

extraction

05

Building graphs with 

Neo4j

06

Comparing RAG vs 

GraphRAG

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/AI Aspirants

  • Data Science/AI Professionals

  • AI/ML/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

About the course

You will learn the following skills by the end of the course:

  • GraphRAG
  • Vanilla RAG
  • Knowledge Graphs
  • Document Chunking
  • Entity Extraction
  • Relation Extraction
  • Pydantic
  • Neo4j
  • Graph Visualization
  • Vector Indexing
  • Hybrid Retrieval
  • RAG Comparison
  • Graph-based Retrieval
  • Multi-hop Question Answering
  • LLM-based Extraction
  • Answer Comparison
  • Retriever Design
  • Vector Search

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!

  • 4.8+Instructor rating

  • 200+ reviews

  • 57K+students

  • 80+ Courses

Launch your GraphyLaunch your Graphy
100K+ creators trust Graphy to teach online
𝕏
Complete Data Science Pathway by ML+ 2026 Privacy policy Terms of use Contact us Refund policy