Graph Data Science in Practice
Welcome to GraphAcademy and the Graph Data Science in Practice workshop.
In this hands-on workshop, you will learn how to apply graph algorithms to solve real business problems in fraud detection and supply chain optimization.
What you will learn
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The fundamentals of Graph Data Science and the GDS Project → Run → Write workflow
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How to create graph projections for different analytical questions
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Community detection algorithms (Louvain, WCC) to uncover fraud rings
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Centrality algorithms (PageRank, Betweenness, Degree) to rank influential nodes
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Pathfinding algorithms (Dijkstra, Yen’s) to optimize supply chain routes
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Node embeddings (FastRP) for machine learning features
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How to build complete citation analysis pipelines with the Python GDS client
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How to run graph analytics at scale with Aura Graph Analytics
Prerequisites
Before taking this workshop, you should have:
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Basic understanding of graph databases and Neo4j
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Familiarity with Cypher query language
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Able to read and execute basic queries in Neo4j Browser
We recommend taking the Neo4j Fundamentals - Learn the basics of graph databases course or the Introduction to Graph Databases workshop.
Duration
4 hours
This workshop includes
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27 lessons
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Multiple demonstration videos
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Live coding exercises
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Real-world datasets: P2P financial transactions (fraud), Cora citations, Cargo 2000 logistics
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Pre-configured sandbox environment with datasets
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Jupyter notebooks for Python GDS client exercises
Get Support
If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for real-time discussions.
Feedback
If you have any comments or feedback on this course you can email us on graphacademy@neo4j.com.
Course Coming Soon
We are currently working on this course. Fill in the form below to register your interest and we will contact you when it is ready.