# Math & Optimizations: Introducing Graphs & Graph Operations

Math    |    Intermediate
• 12 videos | 1h 28m 41s
• Includes Assessment
The graph data structure plays a significant role in modeling entities in the real world. A graph comprises nodes and edges that are used to represent entities and relationships, respectively. A graph can be used to model a social network or a professional network, roads and rail infrastructure, and telecommunication and telephone networks. Through this course, you'll explore graph data structure, graph components, and different types of graphs and their use cases. Start by discovering how to represent directed, undirected, weighted, and unweighted graphs in NetworkX. You'll then learn more about visualizing nodes and connections in graphs using Matplotlib. This course will also help you examine how to implement graph algorithms on all graph types using NetworkX. Upon completing this course, you will have the skills and knowledge to create and work with graphs using NetworkX in Python.

## WHAT YOU WILL LEARN

• discover the key concepts covered in this course
model entities and relationships in the real world using graphs
recognize the different types of graphs, their characteristics, and use cases
create undirected graphs using NetworkX
associate attributes with the graph, individual nodes, and individual edges
create directed graphs using NetworkX
• compute the degree of a graph node
identify predecessors and successors in a directed graph
compute simple cycles, triangles, and edge covers using NetworkX
perform topological sorting in a directed acyclic graph
compute the shortest path and a minimum spanning tree for a graph
summarize the key concepts covered in this course

## IN THIS COURSE

• 3.  Types of Graphs
• 4.  Creating Undirected Graphs Using NetworkX
• 5.  Adding Attributes to Graphs Nodes and Edges
• 6.  Creating Directed Graphs Using NetworkX
• 7.  Computing Degree of a Node
• 8.  Understanding Predecessors and Successors
• 9.  Computing Simple Cycles, Triangles, and Edge Covers
• 10.  Performing Topological Sort
• 11.  Computing Shortest Path and Minimum Spanning Tree
• 12.  Course Summary

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