Graph Data Structures: Understanding Graphs & Knowledge Graphs

Python 3.7    |    Beginner
  • 12 videos | 1h 42m 47s
  • Includes Assessment
  • Earns a Badge
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.

WHAT YOU WILL LEARN

  • 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

IN THIS COURSE

  • 2m 7s
  • 12m 18s
  • Locked
    3.  The Property Graph Model
    6m 15s
  • Locked
    4.  Plain Old Graphs and Knowledge Graphs
    10m 46s
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    5.  Taxonomies and Ontologies
    11m 4s
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    6.  Types of Graphs
    9m 28s
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    7.  Creating and Visualizing an Undirected Graph
    7m 20s
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    8.  Performing Operations on Undirected Graphs
    12m 43s
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    9.  Performing Operations on Directed Graphs
    7m 47s
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    10.  Executing Graph Algorithms I
    8m 13s
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    11.  Executing Graph Algorithms II
    12m 52s
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    12.  Course Summary
    1m 54s

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