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

2,505 ratings
421 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

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.

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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126 - 150 of 411 Reviews for Applied Social Network Analysis in Python

By Landon M L

Oct 24, 2017

Good instruction because the explanation with some good examples that improve my comprehension.

By Wenlei Y

Nov 23, 2019

This course really opens my eye, providing a new standpoint from which we visualize "network".

By Ivan S F

Jun 2, 2019

Very very good course. It provides a brief but comprehensive introduction to network analysis.

By Benjamin R

Jun 9, 2018

Very good insights into social network analysis. I particularly liked the final assignment.

By Rocco C

Oct 9, 2017

Very interesting course, thank you. The assignments could have been a bit more challenging.

By Long T B

Oct 27, 2020

I really appreciate Coursera for offering this course. It is very valuable to my research.

By Estella C

Jul 30, 2020

Very practical course! Explained all the concepts very clear and with meaning examples.

By David T

Jan 4, 2021

I enjoyed the classes in this specialization. I felt that I have learned a great deal.

By Parikshit A D

May 3, 2020

Best Course I have seen, learnt a lot about something to which I was completely new!!!

By Мирзабекян А В

Aug 9, 2018

One of the most interesting and challenging courses in specialization, in my opinion.

By Hiroki U

Nov 30, 2020

Assignment of week4 was tough, but interesting.

Thanks for making such a good course.

By Reed R

Mar 2, 2018

Well taught and in a field which is not covered by many other data science curricula

By Rajesh R

Feb 7, 2018

Excellent course to understand various networking principles and analyszng the same.

By Carlos S

Oct 8, 2017

Great introduction to network theory and applications using Python Networkx library.

By Krzysztof K

Nov 5, 2020

Very informative and useful content was presented in very easy to understand way.

By Ricardo J M S

Jun 1, 2020

It is the best course of the 5 courses of the specialitation. I strongly recommend

By Ferdinand C

Aug 13, 2020

Brilliant instructor! I really learned a great deal from this course. Thank you

By Nicolás S

Jan 3, 2021

Nice topic to learn! Good materiales and tools were providade in thsi course

By Vighneshbalaji

Apr 28, 2020

Very Useful. I learned a lot. Thanks to Coursera and University of Michigan

By Chanaka S

Aug 1, 2020

Lecture is God To Me The Person Who has Good Knowledge then easy to study

By Amila R

Sep 30, 2019

Good starting point for those who want ro learn social network analysis.

By Roberto L L

Mar 26, 2019

It was a wonderful course, linked network's models and machine learning.

By 高宇

Dec 2, 2018

Very Nice Coursera! It lead me to reknow the relations among the worrld.

By Thaweedet

Aug 15, 2018

Great, You will to learn how to develop feature for social network data

By Mischa L

Jan 6, 2018

Great course. Very good homework assignments, but somewhat on easy side