Get started with Graph Data Science
3h
Learn Neo4j Graph Data Science fundamentals hands-on: project graphs, run and configure graph algorithms, and interpret results on a real movie dataset.
Role
Data Scientist
Run graph algorithms on connected data: learn centrality, path finding, and analytics workflows with Neo4j Graph Data Science and Aura Graph Analytics.
Relationships carry signal that feature tables flatten away. Who is connected to whom, how central a node is, which communities form — graph algorithms answer these questions directly, and you feed the results into analyses, dashboards, and machine learning models. These courses cover both ways to run graph analytics with Neo4j: the Graph Data Science (GDS) library inside the database, and Aura Graph Analytics with on-demand compute sessions. Start with Get started with Graph Data Science, then Aura Graph Analytics fundamentals, before going deeper on centrality and path finding.
4 courses~7h
Aura Graph Analytics fundamentals
1h
Learn Aura Graph Analytics: on-demand, session-based graph compute. Run graph algorithms from Cypher, Python, or any driver, isolated from your DB.
Path Finding with GDS
1h
Find shortest paths in Neo4j using Cypher and Graph Data Science. Run Dijkstra and Yen graph algorithms on a weighted airport network, hands-on.
Understand centrality algorithms
2h
Master centrality graph algorithms in Aura Graph Analytics. Sort them into six families, then run each against a real network of 59,798 messages.