Graph Data Structures: Understanding Graphs & Knowledge Graphs

Python 3.7    |    Beginner
• 12 Videos | 1h 42m 47s
• Includes Assessment
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

• 1.
Course Overview
• 2.
Graphs to Model Entities and Relationships
• 3.
The Property Graph Model
• 4.
Plain Old Graphs and Knowledge Graphs
• 5.
Taxonomies and Ontologies
• 6.
Types of Graphs
• 7.
Creating and Visualizing an Undirected Graph
• 8.
Performing Operations on Undirected Graphs
• 9.
Performing Operations on Directed Graphs
• 10.
Executing Graph Algorithms I
• 11.
Executing Graph Algorithms II
• 12.
Course Summary

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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

Digital badges are yours to keep, forever.