IT Skills     Data and Databases     Data Management     Graph Data Structures and Algorithms

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Graphs are used to model a large number of real-world scenarios, including professional networks, flight networks, and schedules. Working in these problem domains involves a deep understanding of how graphs are represented and how graph algorithms work.
Learn the basic components of a graph and how nodes and edges can be used to model relationships. Examine how domains such as social networks, purchases on an e-commerce platform, and connected devices can be modeled using graphs.
Next, explore how to use an organizing principle to add semantic meaning and context to graphs. Discover how to apply higher-level organizing principles to knowledge graphs using taxonomies and ontologies.
Finally, get hands-on experience creating and manipulating graphs, and running graph algorithms using the NetworkX library in Python.
When you have completed this course, you will have a solid understanding of how graphs model entities and relationships in the real world.

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Objectives

Graph Data Structures: Understanding Graphs & Knowledge Graphs discover the key concepts covered in this course use graph nodes and edges to model entities and relationships in the real world recall the attributes of the property graph model used to represent knowledge graphs compare and contrast plain old graphs with knowledge graphs create taxonomies and ontologies by using higher-level organizing principles with knowledge graphs list the different types of graphs and explore their structure create, manipulate, and visualize graphs in NetworkX perform common graph operations to compute adjacent nodes, degree of a node, and check edge connections on undirected graphs perform common graph operations to find predecessors, successors, ancestors, and descendants on directed graphs execute algorithms in NetworkX to compute triangle count, simple cycles in graphs, and test for a directed acyclic graph execute algorithms in NetworkX to perform topological sort, compute the shortest path, and find the minimal spanning tree summarize the key concepts covered in this course