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Learn Graphs and Social Network Analytics Using Python

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Learn Graphs and Social Network Analytics Using Python. This course is absolutely designed for beginners , graph enthusiast ready to analyze the world using graphs

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Descripción

The name of this course is Learn Graphs and Social Network Analytics Using Python. The knowledge you will get with this indescribable online course is astonishing. This course is absolutely designed for beginners , graph enthusiast ready to analyze the world using graphs.
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Theophilus Siameh, one of the very best experts in this field.

Description of this course: Learn Graphs and Social Network Analytics Using Python

Course 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 AnalysisCourse 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.

Requirements of this course: Learn Graphs and Social Network Analytics Using Python

What are the requirements? Basic programming knowledge in python or other language Access to computer and with an internet Fundamentals of Graph Theory

What will you learn in this course: Learn Graphs and Social Network Analytics Using Python?

What am I going to get from this course? Create graphs using 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

Target audience of this course: Learn Graphs and Social Network Analytics Using Python

Who is the target audience? 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

Información adicional

Instructor

Theophilus Siameh

Lectures

66

Length

6.5

Skill Level

All Levels

Languages

English

Includes

Lifetime access <br/> 30 day money back guarantee! <br/> Available on iOS and Android <br/> Certificate of Completion

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