Learning path
Generative AI & GraphRAG
Give your LLMs a knowledge graph memory. Build RAG pipelines that retrieve structured, contextual facts for more accurate, grounded answers.
The curriculum
20 courses, to complete.
A rhythm of deeper courses that teach concepts, and quicker labs that drill a single pattern.
20 Courses · 1–2 hours each
- 01Course2h
Neo4j & GenerativeAI Fundamentals
Start the course - 02Course1h
Introduction to Vector Indexes and Unstructured Data
Start the course - 03Course1h
Building Knowledge Graphs with LLMs
Start the course - 04Course2h
Constructing Knowledge Graphs with Neo4j GraphRAG for Python
Start the course - 05Course1h
Using Neo4j with LangChain
Start the course - 06Course
Build a Neo4j-backed Chatbot using Python
Start the course - 07Course
Build a Neo4j-backed Chatbot with TypeScript
Start the course - 08Course
Building GraphRAG Agents with ADK
Start the course - 09Course
Building GraphRAG Agents with CrewAI
Start the course - 10Course
Build a ReAct agent with Neo4j and LangChain
Start the course - 11Course
Building GraphRAG agents with LangGraph
Start the course - 12Course
Building GraphRAG agents with LangGraph.js
Start the course - 13Course
Evaluating GraphRAG with RAGAS
Start the course - 14Course
Using Neo4j with LlamaIndex
Start the course - 15Course
Using Neo4j with LangChain.js
Start the course - 16Course2h
Building GraphRAG Python MCP tools
Start the course - 17Course2h
Building GraphRAG TypeScript MCP tools
Start the course - 18Course2h
Context Graphs: Agent Memory with Neo4j
Start the course - 19Course2h
Developing with Neo4j MCP Tools
Start the course - 20Course2h
Building Agents in Neo4j Aura
Start the course