Knowledge Graphs — Beginner
Foundational five-day path through property graphs, entity/relationship modeling, Cypher, graph algorithms, and a first GraphRAG system.
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Your First Knowledge Graph
What a knowledge graph actually is — nodes, edges, and properties — how it differs from relational and vector databases, the property-graph vs RDF split, and the multi-hop questions graphs answer that tables can't.
45 minNodes & EdgesProperty GraphsGraph vs Relational - 2
Modeling Entities & Relationships
Designing a graph schema: choosing nodes vs edges vs properties, labels and relationship types, directionality, reification, and the modeling tradeoffs that decide whether your queries stay simple.
55 minOntologySchema DesignEntity Modeling - 3
Querying Graphs with Cypher
The property-graph query model: MATCH / WHERE / RETURN, ASCII-art pattern matching, variable-length and multi-hop paths, aggregation, and CREATE/MERGE — and how it compares to SQL joins.
60 minCypherPattern MatchingMulti-hop Queries - 4
Graph Algorithms for Retrieval
Traversal, shortest path, PageRank and personalized PageRank, community detection, and centrality — the algorithms that power ranking and retrieval over a knowledge graph.
60 minShortest PathPageRankCommunity Detection - 5
Your First GraphRAG System
The beginner capstone — combine graph modeling, Cypher, and graph algorithms with an LLM into a working GraphRAG pipeline: entity linking, subgraph retrieval, context assembly, and generation.
75 minGraphRAGCapstoneEntity Linking