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

4.6
stars
2,703 ratings

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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426 - 450 of 454 Reviews for Applied Social Network Analysis in Python

By Hui X

•

Sep 22, 2022

Easy to follow!

By Thabsheer H

•

Oct 16, 2020

nicely explained

By arpit m

•

Dec 15, 2018

very good course

By Raghunath P

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Nov 10, 2018

Great Course!

By Vinit D

•

Jan 16, 2020

Tough course

By Avi R

•

Aug 3, 2019

Satisfactory

By Jean E K

•

May 18, 2018

good teacher

By TEJASWI S

•

Aug 2, 2019

Good course

By Andreas C

•

Dec 2, 2017

quite good

By Chethan S L

•

Oct 2, 2019

Excellent

By Xing W

•

Dec 3, 2017

Not bad

By shubham z

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Jun 13, 2020

good

By mallikarjuna y

•

May 5, 2020

good

By V B

•

Dec 30, 2020

NA

By Alexandra C

•

Feb 28, 2021

Videos are very distracting as there are many cutscene from the text to the instructor's face which is very disrupting for the flow of the lecture. Maybe overlaying his face on a small window on the corner will be better

By Daniel B

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Dec 18, 2020

This course feels more like an API summary of networkx rather than a real course on social network analysis. On top of that, the course uses the outdated networkx 1.11, while 2.0 has been out for over three years.

By Ying X T

•

Mar 5, 2024

Good introduction but wish the assignments were more challenging and intuitive felt like it was a lot just like heres some code to do what you need to do

By Jeremy .

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Jan 1, 2021

Some of the assignment organization could have been better, but otherwise the information was rock solid!

By József V

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May 4, 2018

Useful but weaker comparing to Pandas or Scikit courses.

By Sara C

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May 16, 2018

i like the way that lecturer teach.

By Leon V (

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Oct 7, 2017

it was okay, 3.5 really

By DW J

•

Apr 6, 2018

hm..

By Luis B

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Nov 20, 2022

I thought the content was interesting - but it is so stale, none of the packages work with conventional language semantics. Getting assigments to submit was a major pain, ultimately souring the experience.

By Afreen F

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Feb 7, 2021

Lecture Videos are good but it seems 0 efforts were put in the assessments. The auto-grader is especially a pain and you end up spending LOT of time around trivial issues with the auto-grader.

By MENAGE

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Feb 22, 2021

Aimerais avoir plus de temps et de conseils pour bien réussir..