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

4.7
stars
2,377 ratings
397 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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126 - 150 of 387 Reviews for Applied Social Network Analysis in Python

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 F S C

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

By Rui

Oct 11, 2017

very good introductory course for social network analysis using 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 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