Graph Data Structures: Understanding Graphs & Knowledge Graphs

Python    |    Beginner
  • 12 videos | 1h 42m 47s
  • Includes Assessment
  • Earns a Badge
Rating 4.5 of 29 users Rating 4.5 of 29 users (29)
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
    In this video, you will use graph nodes and edges to model entities and relationships in the real world. FREE ACCESS
  • Locked
    3.  The Property Graph Model
    6m 15s
    Upon completion of this video, you will be able to recall the attributes of the property graph model used to represent knowledge graphs. FREE ACCESS
  • Locked
    4.  Plain Old Graphs and Knowledge Graphs
    10m 46s
    In this video, learn how to compare and contrast regular graphs with knowledge graphs. FREE ACCESS
  • Locked
    5.  Taxonomies and Ontologies
    11m 4s
    In this video, find out how to create taxonomies and ontologies by using higher-level organizing principles with knowledge graphs. FREE ACCESS
  • Locked
    6.  Types of Graphs
    9m 28s
    Upon completion of this video, you will be able to list the different types of graphs and explore their structure. FREE ACCESS
  • Locked
    7.  Creating and Visualizing an Undirected Graph
    7m 20s
    In this video, you will learn how to create, manipulate, and visualize graphs in NetworkX. FREE ACCESS
  • Locked
    8.  Performing Operations on Undirected Graphs
    12m 43s
    In this video, find out how to perform common graph operations, such as computing adjacent nodes, degree of a node, and checking edge connections on undirected graphs. FREE ACCESS
  • Locked
    9.  Performing Operations on Directed Graphs
    7m 47s
    Learn how to perform common graph operations to find predecessors, successors, ancestors, and descendants on directed graphs. FREE ACCESS
  • Locked
    10.  Executing Graph Algorithms I
    8m 13s
    During this video, you will learn how to execute algorithms in NetworkX to compute triangle count, simple cycles in graphs, and test for a directed acyclic graph. FREE ACCESS
  • Locked
    11.  Executing Graph Algorithms II
    12m 52s
    Learn how to execute algorithms in NetworkX to perform topological sort, compute the shortest path, and find the minimum spanning tree. FREE ACCESS
  • Locked
    12.  Course Summary
    1m 54s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Book Graph Algorithms for Data Science: With examples in Neo4j
Course CompTIA Data+: Data Visualization Reports
Rating 5.0 of 6 users Rating 5.0 of 6 users (6)
Book Python for Engineering and Scientific Computing

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course Python Development: Getting Started with Programming in Python
Rating 4.6 of 2165 users Rating 4.6 of 2165 users (2165)
Course Senior Professional in Human Resources: Talent Acquisition
Rating 4.7 of 172 users Rating 4.7 of 172 users (172)
Course Generative AI and Its Impact to Everyday Business
Rating 4.6 of 893 users Rating 4.6 of 893 users (893)