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Applied Social Network Analysis in Python, University of Michigan

4.6
1,010 ratings
173 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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167 Reviews

By ABDUL NASIR MUNIRU

Mar 12, 2019

Gave me a very good understanding of the basic concepts

By Varga Imre Károly

Mar 09, 2019

It was great introducing the networks, but I found most of the assignments too straightforward except for the last weeks.

By Akash Gupta

Mar 03, 2019

good

By Aya

Feb 26, 2019

The course covered many relevant topics and was very easy to follow and apply to the real world.

By PREMAL MEHTA

Feb 24, 2019

Excellent delivery and content.

By Daniel Wlazło

Feb 19, 2019

Great course, maybe even the best on this great specialization!

By Agnes He

Feb 19, 2019

Great course. The lectures are taught clearly.

By Kristin Abkemeier

Feb 15, 2019

A nice intro to networks in Python

By CMC

Feb 14, 2019

This is a great course for 2 reasons. The earlier assignments were just difficulty enough to reinforce the lectures. The last assignment was challenging enough to bring the entire specialization to to satisfying close. After finishing assignment 4, I really feel that I can apply the learning from this specialization to real work.

By Martin Huang

Feb 06, 2019

Great course!