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

2,492 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

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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351 - 375 of 410 Reviews for Applied Social Network Analysis in Python

By Gregory C

Apr 4, 2020

Pretty well designed course, except that I found myself battling the auto-grader too often.

By Mohit M K

Oct 22, 2018

One of the more tougher courses in Social Networks but still would recommend to everyone!

By Anad K

Nov 16, 2018

Good Content! And the assignments were just right to augment effective learning.

By Juan M

Jun 11, 2019

The machine learning connection could have been mentioned earlier in the course

By Minshen C

Dec 25, 2019

it would be great if some case study of prediction can be added to the course

By Jonas N

Oct 5, 2018

Highly valuable course and a good starter for network analysis. Do recommend!

By Divyansh R

May 12, 2020

Great instructor. Very engaging videos and thought-provoking assignments.

By Miguel C

Dec 8, 2017

The last assigment is really interesting, all the others are really easy

By Maciej W

Sep 7, 2018

Great hands on learning experience to social network analysis in Python

By Deepalakshmi K

Jun 24, 2019

Daniel Romero is probably the best instructor in this specialization

By Lorenzo V ( R P

May 22, 2021

Great class but, please, fix the autograder, guys. No, really do.

By Roger v S

Oct 6, 2020

The lecturer was the best of the lecturers in the specialisation.

By Carlos F S B

Aug 19, 2020

it was really difficult for me, gotta practice more on my own

By Jesús P

Jan 22, 2018

Good course but could be improved with realistic scenarios.

By Siwei Y

Sep 21, 2017

老师讲解的非常好 , 逻辑清楚,条理明晰。建议编程作业稍微有点难度。所以扣掉一颗星。 希望越来越好。

By Yang F

Sep 22, 2017

The first three weeks are very well planned.

By Christian E

Mar 27, 2019

Very new on this topic and very interesting

By David W

Oct 12, 2017

Challenging course and great instruction.

By Brian R v K

Oct 23, 2017

Great fun, with practical application.

By Robert S

Nov 29, 2020

Interesting material well presented.

By Oscar F R P

Aug 30, 2020

Really hard but very interesting.

By Cyrus N A P

Jan 24, 2019

Well the subject was really hard.

By Deni M

May 30, 2021

G​reat course highly recommended

By Rupert

Jan 23, 2018

Good introduction into graphs!

By Selvakumar

Jun 20, 2018

This is awesome course!