This course is absolutely designed for beginners , graph enthusiast ready to analyze the world using graphs

Summary

This comprehensive course on graph theory and social network analytics is tailor-made for beginners and graph enthusiasts eager to delve into the world of data analysis using graphs. Participants will learn how to create graphs using the NetworkX package in Python, covering fundamental concepts such as nodes, edges, and graph attributes.

Through engaging lectures, quizzes, tests, and real-world assignments, students will explore various graph types and metrics, including clustering coefficient, betweenness centrality, and degree centrality. The course also delves into advanced topics such as connected graphs and bipartite graphs, with a focus on their application in social network analysis.

With over 55 lectures and 6 hours of content, this course provides a comprehensive understanding of graph theory and its practical applications. Participants will gain the skills to analyze social networks like Facebook and Twitter, visualize graphs using different plot types, and extract useful information from complex networks.

Ideal for beginners with little programming experience, intermediate Python programmers looking to enhance their skills, and mathematics students eager to apply their knowledge in real-world scenarios, this course offers lifetime access and promises to be a valuable asset in both career advancement and knowledge enrichment.

 

What You’ll Learn

  • Create graphs using the NetworkX package
  • Create nodes of a graph
  • Create edges of a graph
  • Determine the attributes of a node and edges
  • Analyze social networks like Facebook and Twitter
  • Students will learn more about properties of a graph
  • Learn about Clustering coefficient , Betweenness centrality, degree centrality etc.
  • Learn about Connected graphs, Bipartite graphs, etc.
  • Learn about the types of graphs used for social network analysis

 

Requirements

  • Basic programming knowledge in python or other language
  • Access to computer and with an internet
  • Fundamentals of Graph Theory

Description

BRAND NEW COURSE IS HERE ! Learn Graphs and Social Network Analytics .Become a graph and social analyst today. This is a comprehensive course , simple and straight forward for python enthusiast and those with little python background. You want to learn about how to draw graphs and analyze them, this is the course for you. This course will contain some quizzes, test and some homework assignments, as well as some real world assignment projects. There is over 55 lectures and about 6hours to complete the course. This course comes with live coding screenshots using iPython Notebook .Below is the list of the course summary

  • Overivew of networkX
  • Install networkX module and iPython Notebooks
  • Create nodes
  • Add edges to nodes
  • Getting attributes from a graph
  • Manipulate your graphs ie.; remove nodes /edges
  • Create DiGraphs/MultiGraphs/MultiDiGraphs
  • Graph Generators
  • Graph metrics ; shortest path/clustering coefficient
  • Define functions
  • Visualize graphs
  • Calculate nodes/degree/centrality metrics
  • Some random graphs
  • Small famous graphs
  • Reading and writing graph files
  • Social network analysis
  • Subgraphs
  • Facebook Social Network Analysis

Course goals:

  • At the end of the course students should be able to learn some basics of graph theory
  • Students should be able to analyze Facebook social networks
  • Students should take the simple quizzes
  • Students should know what is directed and undirected graphs
  • Students should be able to visualize graphs using different graph plots
  • You can use this course to analyze the world as a network
  • Everything in this world is now connected
  • Extract useful information from graphs

Life time access to the course. What are you waiting for? Learn practical graph and social network analytics today that would improve your career and increase your knowledge.

Who this course is for:

  • Beginners who have never programmed in python before
  • Students who are Graph Enthusiast
  • Intermediate python programmers who want to level up their skills
  • Students who want to analyze social networks like Facebook and Twitter
  • Mathematics students who wants to apply their knowledge in Graph Theory

 

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