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Applied Social Network Analysis in Python, University of Michigan

4.6
900 ratings
158 reviews

About this Course

This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem. This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

Top reviews

By JL

Sep 24, 2018

It was an easy introductory course that is well structured and well explained. Took me roughly a weekend and I thoroughly enjoyed it. Hope the professor follows up with more advanced material.

By CG

Sep 18, 2017

Excellent tour through the basic terminology and key metrics of Graphs, with a lot of help from the networkX library that simplifies many, otherwise tough, tasks, calculations and processes.

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153 Reviews

By Nikolay Stoychev

Jan 02, 2019

The course and the tutor are great.

I learned how to create and manage network graphs using python with networkx. I was really satisfied from the last week assignment when I had to work with real-life example plus machine learning classifier.

By Sagar

Dec 29, 2018

Grate for solving network analytics issues

By Phillip Lee Chrisman

Dec 26, 2018

Just the greatest class to sum up what is going on in the crazy network media and using what we have learned.

By Suyash Dewangan

Dec 19, 2018

An excellent course that provides a fair knowledge of social networks, the NetworkX package and how to work with networks in Python.

By Robert J King

Dec 19, 2018

The course starts off a bit slow but gets you used to the NetworkX module. The last exercise is a pretty neat culmination of the this course and specialization. It would have been cool for it to also involve text mining, but I enjoyed it and the course in general.

By Michael K.

Dec 17, 2018

Great job!

By Arpit Maheshwari

Dec 15, 2018

very good course

By Diego Trujillo Bedoya

Dec 11, 2018

very useful and engaging. A was hoping a very different scope on the course but this approach did very well.

By Bart T Cubrich

Dec 10, 2018

Great course! Love the instructor. Good background in networks, while sticking to the applied side of things.

By Wei Wu

Dec 09, 2018

This is by far my favorite Coursera course - well organized contents and intuitive example!