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學生對 密歇根大学 提供的 Applied Social Network Analysis in Python 的評價和反饋

4.6
1,428 個評分
230 個審閱

課程概述

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....

熱門審閱

NK

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.

JL

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.

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76 - Applied Social Network Analysis in Python 的 100 個評論(共 222 個)

創建者 Frank L

Oct 14, 2017

This course was very interesting and well taught, finally after all other courses I have managed to complete the assignments for this one in the recommended amount of time. Maybe the questions were structured better than past modules, or maybe my level of understanding of programming in python was at its best. Either way the assignments were very enjoyable, thank you!

創建者 Cong L

Apr 05, 2018

Very clear explanation.

創建者 Carlos S

Oct 08, 2017

Great introduction to network theory and applications using Python Networkx library.

創建者 Luiz H Q L

Sep 25, 2017

Great course, very informative. Thanks!

創建者 Landon M L

Oct 25, 2017

Good instruction because the explanation with some good examples that improve my comprehension.

創建者 Jorge A S

Feb 27, 2018

Great explanations. The instructor is awesome and has good visual material. In-video quizzes keep you engaged during the lecture. I am very happy with the course.

創建者 Dan S

Feb 25, 2018

I loved this course. It was well taught and had excellent problem sets and quizzes to internalize the learning. The material is very relevant to the market today. I highly recommend it.

創建者 Li T

Feb 09, 2018

inspirational course

創建者 David K

May 08, 2018

Amazing class. I loved this.

創建者 Christos G

Sep 18, 2017

Excellent tour through the basic terminology and key metrics of Graphs, with a lot of help from the networkX library that simplifies many, otherwise tough, tasks, calculations and processes.

創建者 周志凌

Jul 05, 2018

good course

創建者 Manuel T

Jan 30, 2018

good stuff. Assignments are a little bit too easy though.

創建者 Amita D

Jun 21, 2018

Very nice course......

創建者 Devon H

May 05, 2018

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

創建者 Jiunjiun M

Apr 14, 2018

I learned many interesting new concepts in social network analysis and a bunch of new graph algorithms, which are rarely taught in the "traditional" algorithm course. Now I know how companies like Cambridge Analytics can use the Facebook's social network data to derive useful information. (It's actually quite easy.) A class like this is more important than ever. I just wish we could have more time to explore a few topics more deeply.

創建者 Juan C E

Nov 11, 2017

Excellent course. Very clear explanations and materials. The assignments were not as difficult as in other courses of the specialization, and very helpful to understand the contents. I highly recommend this course and the specialization.

創建者 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!

創建者 Sanjay K

Jan 22, 2018

Michigan course everything is excellent. love it

創建者 Iurii S

Feb 17, 2018

A great introduction to network analysis. Assignments are easy, but provide a good first glimpse at the topic.

創建者 Brian L

Apr 18, 2018

Really enjoyed the mathematical component of this course. It was fun to see how you could connect the graph theoretical components to the machine learning concepts from earlier courses.

創建者 Gerardo M C

Nov 18, 2017

Nice!

創建者 Víctor L

Mar 23, 2018

Excellent Course, very interesting, no idea that so many tools existed for network study and analysis. Excellent job both from the professor Daniel, and from Coursera/University of Michigan State. The QUIZES were very challenging, sometimes more than the Assignments. I'm really satisfied.

創建者 Ayush R

Aug 05, 2018

Better Explanation, Not too hard to solve .

創建者 Manuel A

Aug 22, 2018

Very challenging and comprehensive course, also directly applicable to machine learning problems, as an example, the last assignment applies network knowledge to extract features and exploit them in predictive modelling problems

創建者 Jan Z

Sep 07, 2018

Great course. Thank you!