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Graph Theory

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4

Graph Theory

Master Graph Theory from scratch with this self-paced online course

updated on icon Updated on Apr, 2024

language icon Language - English

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category icon IT & Software,IT Other

Lectures -98

Duration -7 hours

4

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Course Description

This online course provides a  detailed introduction to the principles of graph theory. It discusses various graph types, their characteristics, terminology, trees, graph traversability, the idea of graph coloring, various methods for representing graphs, the idea of algorithms, and various graph theory-based algorithms.

Students who are interested in learning about the foundations and algorithms of graph theory should use this course. This course will be very helpful for readers who are interested in Language Processing or Computer Networks, physical sciences, or many other subjects because Graph Theory has a wide range of engineering applications.

Goals

What will you learn in this course:

  • Understand the basic concepts of graph theory
  • Apply graph theory algorithms to solve real-world problems
  • Use graph theory to model and analyze complex systems
  • Discover the different graph theory tools and technologies.
  • Master the different graph theory best practices.

Prerequisites

What are the prerequisites for this course?

  • Basic understanding of mathematics, including sets, relations, and functions
  • Basic understanding of computer science, including algorithms and data structures
Graph Theory

Curriculum

Check out the detailed breakdown of what’s inside the course

Graph Theory
1 Lectures
  • play icon Graph Theory And It's Application - Getting Started 01:48 01:48
Graph Theory Introduction
3 Lectures
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Graph Theory Fundamentals
7 Lectures
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Graph Basic Properties
2 Lectures
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Types of Graph
12 Lectures
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Trees
6 Lectures
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Graph Coloring
3 Lectures
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Graph Isomorphic
2 Lectures
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Graph Traversibility
7 Lectures
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Graph Representation Techniques
7 Lectures
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Algorithm and Complexity Analysis
8 Lectures
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Algorithm and Classification
13 Lectures
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Graph Theory Algorithm
26 Lectures
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Instructor Details

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