GraphAcademy Knowledge Graph and GraphRAG Course

Overview

GraphAcademy offers free online courses on Knowledge Graph and GraphRAG, teaching developers how to build RAG systems that leverage the power of graph databases for more accurate and explainable retrieval.

Course Topics

• Knowledge Graph Fundamentals: Understanding graph data models and relationships
• GraphRAG Architecture: Combining graph traversal with vector search
• Neo4j Integration: Using Neo4j for knowledge graph storage
• Vector Search: Implementing semantic search with embeddings
• Hybrid Retrieval: Combining graph queries with vector similarity
• Query Generation: Text-to-Cypher for natural language queries
• Production Deployment: Best practices for enterprise GraphRAG systems

Learning Path

1. Introduction to Knowledge Graphs
2. Building Knowledge Graphs from Text
3. Vector Search Fundamentals
4. Integrating Vector Search with Graph Queries
5. Advanced GraphRAG Patterns
6. Evaluation and Optimization
7. Production Deployment

Key Takeaways

• How to model domain knowledge as a graph
• Combining structured (graph) and unstructured (vector) data
• Multi-hop reasoning through graph traversals
• Explainable AI through graph relationships
• Enterprise-grade GraphRAG implementation

Target Audience

• AI/ML engineers building RAG applications
• Data engineers working with knowledge graphs
• Developers interested in advanced retrieval techniques
• Enterprise architects designing AI systems

Hands-On Practice

Courses include practical exercises with Neo4j sandbox environments, allowing students to build real GraphRAG applications.

Pricing

Free online courses from Neo4j.