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Applied Social Network Analysis in Python に戻る

ミシガン大学(University of Michigan) による Applied Social Network Analysis in Python の受講者のレビューおよびフィードバック



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....



May 03, 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 24, 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.


Applied Social Network Analysis in Python: 151 - 175 / 343 レビュー

by Su L

Mar 30, 2020

enjoyed it very much, thank you Professor and mentors

by Nishal

Dec 04, 2019

Good information, at a good pace, explained very well

by PURNA C R . K

Jul 23, 2020

Indepth knowledge about network analysis. Thank you


Oct 21, 2019

the very best course it is very helpful and useful


Jun 11, 2020

Very useful course especially for the beginners .

by Jun W

Aug 19, 2018

A very interesting course, beyond my expectation.

by Sanjay K

Jan 22, 2018

Michigan course everything is excellent. love it

by Eric W

Feb 03, 2020

Clear, concise, well organised and structured.

by Sebastian B B

Aug 24, 2020

Manual calculation for quizes are useless imo

by Xin Y

Apr 04, 2020

Excellent Course! Best in the specialization!

by Konstantinos M

Sep 13, 2018

Very interesting topic and well-made lessons.

by phantomxx

Oct 09, 2020

Great content and practices! Really useful.

by Mohammad H

Oct 26, 2018

the course will teach basic of SNA so clear

by Ayush R

Aug 05, 2018

Better Explanation, Not too hard to solve .

by Fengping W

May 01, 2018

It is really a good series, I learned a lot

by Sagar

Dec 29, 2018

Grate for solving network analytics issues

by John A C

Nov 18, 2019

I loved learning all about graph theory!

by Luiz H Q L

Sep 25, 2017

Great course, very informative. Thanks!

by Bruce M

Apr 27, 2020

Great course, Interesting assignments.

by Behzad M

Jan 19, 2020

Very interesting, I have learnt a lot.

by Dongquan S

Oct 22, 2019

Very well organized course. Thank you!

by Tina L

Dec 16, 2017

Good Elaboration. Very clear concepts.

by Ivan

Jul 07, 2020

Was an Intresting and awesome course

by chenshenyou

Apr 13, 2020

very nice graph training, good work!

by Ho C

May 30, 2019

Great course with clear instructions