Cypher Indexes and Constraints
2h
Speed up Neo4j queries with Cypher constraints and indexes: uniqueness, node keys, range, composite, text, and full-text indexes, all hands-on.
Topic
Processing
Import and process graph data in Neo4j: load CSV files with Cypher, tune indexes and constraints, and build knowledge graphs from unstructured text.
Before you can query a graph, you have to build one. Processing covers the pipeline that turns raw data — CSV exports, relational tables, documents — into a well-structured, performant Neo4j graph: importing records, adding the indexes and constraints that keep queries fast and data consistent, and using large language models to extract entities from unstructured text. Start with Importing CSV data into Neo4j, follow it with Cypher Indexes and Constraints, then tackle unstructured data with vectors and LLM-built knowledge graphs.
5 courses~7h
Importing CSV data into Neo4j
1h
Write Cypher that imports CSV data into Neo4j. Create nodes and relationships with LOAD CSV, cast data types, and batch large imports in transactions.
Introduction to Vector Indexes and Unstructured Data
1h
Learn semantic search with Neo4j vector indexes. Create embeddings with LLMs, chunk unstructured data with LangChain, and build a knowledge graph.
Building Knowledge Graphs with LLMs
1h
Start building knowledge graphs with LLMs. Use the Neo4j LLM Graph Builder to turn unstructured text into a knowledge graph and query it with Cypher.
Constructing Knowledge Graphs with Neo4j GraphRAG for Python
2h
Construct knowledge graphs from unstructured data with Neo4j GraphRAG for Python. Define schemas, tune chunking, and build GraphRAG retrievers.