# Neo4j: Building Graphs with Neo4j's Graph Data Science Library

Neo4j    |    Beginner
• 12 videos | 1h 46m 17s
• Includes Assessment
Rating 3.7 of 3 users (3)
The Graph Data Science (GDS) library provides data scientists and developers with the necessary tools to perform powerful analysis of their graph data. In this course, you will look at various use cases of GDS and cover some of its essential operations. Begin with an overview of the GDS library and then dive into using the library by building in-memory graphs from the contents of your Neo4j database. Explore how to build graphs using native and Cypher projections. Next, apply a graph algorithm to your GDS graph and see how it can be used to obtain meaningful information about the nodes and relationships in your data. After completing this course, you will have a fundamental understanding of the GDS library for Neo4j and the necessary capabilities to build your own in-memory graphs and extract significant insights.

## WHAT YOU WILL LEARN

• Discover the key concepts covered in this course
List the main categories of graph algorithms and recall their use cases
Recognize the mechanism of creating and working with graphs in neo4j's graph data science library
Install the graph data science library for a neo4j dbms
Create an in-memory graph using the native projection configuration for nodes and relationships
Use the page rank algorithm to compute a score for each node in a graph
• Load properties from a source database to an in-memory graph
Apply a graph data science function to read a property from a graph
Build a graph using the cypher projection by setting node and relationship queries
Create a cypher projection graph with properties from the source database
Build a sub-graph containing a subset of elements from an already existing graph
Summarize the key concepts covered in this course

## IN THIS COURSE

• 3.  Using the Graph Data Science Library
• 4.  Setting Up the Graph Data Science Library
• 5.  Creating a Graph with Native Projection
• 6.  Applying a Page Rank Algorithm on a Graph
• 7.  Projecting Properties in a Graph
• 8.  Accessing Properties from a Graph
• 9.  Creating Cypher Projection Graphs
• 10.  Building Cypher Graphs with Properties
• 11.  Building Subgraphs
• 12.  Course Summary

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