Neo4j Graph Data Science

Neo4j Graph Data Science

Course Description

As data science continues to be increasingly relevant for enterprises globally, graph technology and algorithms have emerged as powerful tools for answering complex questions based on connections and patterns resident in corporate data sets. Using the Neo4j Graph Data Science Library, data scientists are able to work with complex data in ways that are not always practical or even possible at scale with SQL queries or other database tools.

In this advanced Neo4j training, you’ll learn how data scientists are leveraging graph database technology and algorithms to drive real-time decision making and planning.

Through this course you will:

• Learn about Neo4j, the Labelled Property Graph model and the Neo4j Graph Data Science Library (GDS)

• Prepare your development environment for using the Neo4j GDS

• Perform exploratory data analysis and understand best practices for using Neo4j GDS

• Write code to implement these types of graph algorithms: - Community Detection - Centrality - Pathfinding - Similarity - Link Prediction - Visualize results using Neo4j Bloom

Please note: This is a BY INVITATION ONLY event.

• Format: Instructor-led, online event with hands-on exercises
• Duration: 7 Hours
• Audience for this course: Data Scientists, Data Analysts, Data Engineers

Technical requirements

• Neo4j GDS Training will include hands-on exercises which leverage software and working examples that are hosted in the Neo4j Online Sandbox system.
• You will need your own laptop and will need access to Zoom Conferencing. Please note that some companies block the use of Zoom on their equipment and internal networks. Check with your company if using Zoom will be an issue as you will need to use a personal pc to access the training.

Recommended reading and available resources

Review information on neo4j.com on the Neo4j Graph Data Science Library