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Learner Reviews & Feedback for Applied Social Network Analysis in Python by University of Michigan

4.7
stars
2,491 ratings
420 reviews

About the 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

NK
May 2, 2019

This course is a excellent introduction to social network analysis. Learnt a lot about how social network works. Anyone learning Machine Learning and AI should definitely take this course. It's good.

JL
Sep 23, 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.

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151 - 175 of 410 Reviews for Applied Social Network Analysis in Python

By Dirisala S

Jul 22, 2019

The have lot of stuff to learn. It will definitely enhance your skill.

By Dibyendu C

Oct 19, 2018

Well structured and quality lecture content with excellent assignments

By Nikhil N

Jul 18, 2021

W​onderful course with very detailed explanations!!! Simply wonderful

By Liran Y

May 20, 2018

Interesting and fun. Daniel's lecturing style is clear and enjoyable.

By Chiau H L

Apr 4, 2019

Awesome course!!! Helped me a lot to get started with graph analysis

By Keqi L

Apr 14, 2019

Interesting slides and knowledge. e.g. Page rank is super cool!!!!

By Kai H

Nov 8, 2018

Good course, may be better if offer more practice and application.

By Tatek E

Mar 23, 2020

Excellent presentation, exercise and reading materials. Thank you

By wenzhu z

Feb 22, 2018

very clear logic, and will always wrap up at the end of the class

By 杨志陶

May 17, 2020

A practical way to learn social network analysis. Great course!

By Renzo B

Sep 23, 2019

I learned a lot of things that I can apply to my line of work.

By charles l

Feb 4, 2019

A completely new area for me, and a really fascinating course.

By Yee F

Jul 1, 2021

Course is much easier to understand that applied text mining.

By Haris P D

Jan 31, 2020

One of the most awesome course that I have taken on Coursera!

By Wai Y P S

Jun 22, 2021

Thanks you so much University of Michigan for Great course

By Marco Z

Apr 22, 2020

Very interesting , a new point of view for future analysis!

By Israel D D G

Aug 22, 2020

Excellent course, good technical and teoretical knowledge.

By LEE D D

Nov 5, 2017

Excellent! It was one of the great assignments I ever had!

By Manuel T

Jan 30, 2018

good stuff. Assignments are a little bit too easy though.

By Jiahui B

Nov 28, 2017

Very useful course. It helps me finish my course project.

By Ruihua G

Jul 8, 2019

this course provided a overview of the network analysis.

By Jiefei W

Apr 11, 2020

Practiced with what was covered in the 1th~3rd courses.

By Abdul N M

Mar 12, 2019

Gave me a very good understanding of the basic concepts

By Manuel V

Oct 16, 2018

in my opinon, the best of the specialization. thank you

By Maryanne K

May 4, 2020

Outstanding explanation of concepts. Highly recommend.