Chevron Left
Back to Applied Social Network Analysis in Python

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

4.7
stars
2,243 ratings
366 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.

Filter by:

76 - 100 of 355 Reviews for Applied Social Network Analysis in Python

By Lutz H

Jul 19, 2019

Great course! Really well explained with intuitive examples and great illustrations. At the end there is an interesting but challenging assignment.

By Devon H

May 5, 2018

Great lecturer, comprehensive material and unlike other courses in this specialisation, actually prepares you well for the assignments and quizzes.

By Atilio T

Mar 22, 2020

Excellent course. The lecturer explains in a simple way to understand, and exercise are interested to the analysis of social network using python.

By Vincenzo T

May 16, 2019

Very good course! I was afraid going into this after going the rather bad "Text Mining". However, it was super fun, well done and informative!

By Vladimir

Dec 29, 2017

A very good course to learn about networks. Thanks!

The cherry on top was to apply machine learning techniques to predict how the net evolves.

By Teo S

Oct 22, 2017

Best course in the series. The lecturer managed to explain difficult concepts very clearly through its excellent slides and words. Thank you!

By Vinicius d A O

Mar 16, 2020

This course was fantastic, with a lot of information and tips important for me. The instructor is very focused and I have confidence on him.

By Γεώργιος Κ

May 15, 2018

Another must to have lesson from Michigan Univeristy. After completing this lesson the Social Networks will be an analysis challenge.

By Suyash D

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 Kueida L

Sep 3, 2020

The quizzes were not giving you free points like other online courses. They were challenging. The assignments were well-structured.

By Thales A K N

Jul 8, 2020

Very cool knowledge!! Began the specialization not knowing that this kind of study existed, and it was awesome learning about it!!

By Henri

May 19, 2019

Great intro to networks; last assignment is challenging but is a good opportunity to put everything together (python+ML+Network).

By MARKANTI B S

Sep 21, 2020

The concept and assignment are excellent .This lectures gives good idea about usage networkx . Overall the course is excellent .

By Elias

Jan 11, 2018

This is a very informative course in the property of networks and the feature extraction you can obtain out of this. Excellent

By Shiomar S C

Nov 5, 2019

Excelente course, the instructor really meks you undestand with the right structure and having meaningfull in video quizes

By CasulGamer

Jun 11, 2019

One of the best courses on social network analysis. Professor Daniel Romero did an excellent job explaining the contents.

By Varga I K

Mar 9, 2019

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

By Mile D

Dec 20, 2017

Excellent explanations and examples. Recommended text to read was also very helpful. Thanks for providing this course!!!

By Sarah H H

Jun 3, 2019

i found this course to be fun and straightforward. The assignments were directly aligned to instruction. Great course!

By Christian P

Dec 29, 2019

Excellent, well taught and in-depth programming exercises. I really got my hands into programming with networkx here.

By Oscar J O R

Oct 15, 2017

A really good course. Notebooks could be very useful to practice and maybe more exercises(not graded) with real data.

By Bhavraaj S

Jun 4, 2020

But why am i not getting certififcate of completion.I need it with tthe course which holds more value than learning

By Slavisa D

Jun 9, 2019

Very helpful, I didn't know anything about graphs, networks modelling and the NetworkX package before this course.

By Juan M

May 31, 2020

Nice, delves on graph theory in quite an intuitive way, with exercises on Python. Can be recommended to a friend

By Yunhong H

Mar 23, 2019

Great course. The lectures are taught clearly. The knowledge gained in this course is very useful in real world.