Applied Algorithms in GDS
Course Description
This course demonstrates how to apply GDS algorithms to solve real-world industry problems.
You’ve learned the fundamentals of graph projections, algorithm execution, and configuration in the Getting Started with GDS course. Now you’ll see these techniques solve actual challenges across manufacturing, fraud detection, logistics, research, and machine learning.
Each module focuses on a different industry use case, showing not just how to run algorithms, but when and why professionals choose specific approaches. You’ll work with realistic datasets, implement complete analytical workflows, and understand the business reasoning behind each technique.
By the end of this course, you’ll be able to design and implement graph-based solutions for complex industry problems.
The course automatically creates a new movie recommendations sandbox within Neo4j Sandbox that you will use throughout the course.
Prerequisites
This course is intended for analysts and data scientists who have:
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Completed Getting Started with GDS or equivalent experience
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Understanding of graph projections (monopartite, bipartite, multipartite)
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Familiarity with algorithm execution modes (stream, write, mutate)
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Basic knowledge of algorithm configuration (orientation, weights)
Duration
4-5 hours
What you will learn
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Manufacturing optimization: Use centrality and community detection for root cause analysis in production systems
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Fraud detection: Build network-based fraud identification systems using graph patterns
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Supply chain logistics: Optimize routes and logistics with pathfinding algorithms
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Citation networks: Map research influence and identify key papers using centrality measures
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Node embeddings: Create structural representations for machine learning pipelines
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.