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Applied Social Network Analysis in Python(으)로 돌아가기

미시건 대학교의 Applied Social Network Analysis in Python 학습자 리뷰 및 피드백

4.6
별점
1,738개의 평가
286개의 리뷰

강좌 소개

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....

최상위 리뷰

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.

필터링 기준:

Applied Social Network Analysis in Python의 279개 리뷰 중 51~75

교육 기관: 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.

교육 기관: 谢仑辰

Mar 23, 2018

I really appreciate that you offer me such a great specialization of courses.Since I've finished the final course eventually, I should offer my gratitude to you.

교육 기관: Fabrice L

Nov 23, 2017

Very good class.

The lecturer is amazing!! The quizzes help you understand the concepts. The assignments are a little basic though.

Overall you learn a great deal.

교육 기관: PATIL P R

Apr 25, 2020

Very nice platform to learn & enhance skill. Thanks to Prof. and team.. Also thanks to university and coursera platform for providing such a big platform to us.

교육 기관: Jiaqi d

Dec 15, 2019

Really helpful. Get a basic idea of the social network and how to use python to analyze it. Will definitely dig deeper and see how it could relate to my work .

교육 기관: Piyush V

Jan 29, 2020

All over the course is very relevant to what is a need in industry. Very nice video lectures, to the point and crisp. Material is quite informative too.

교육 기관: Matthew J

Jun 04, 2018

An excellent course which is well planned and executed! If you're following the specialization, it's a welcome relief after the text analysis course.

교육 기관: Lutz H

Jul 19, 2019

Great course! Really well explained with intuitive examples and great illustrations. At the end there is an interesting but challenging assignment.

교육 기관: 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.

교육 기관: Atilio T

Mar 22, 2020

Excellent course. The lecturer explains in a simple way to understand, and exercise are interested to the analysis of social network using python.

교육 기관: Vincenzo T

May 16, 2019

Very good course! I was afraid going into this after going the rather bad "Text Mining". However, it was super fun, well done and informative!

교육 기관: Vladimir

Dec 29, 2017

A very good course to learn about networks. Thanks!

The cherry on top was to apply machine learning techniques to predict how the net evolves.

교육 기관: 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!

교육 기관: Vinicius d A O

Mar 16, 2020

This course was fantastic, with a lot of information and tips important for me. The instructor is very focused and I have confidence on him.

교육 기관: Γεώργιος Κ

May 15, 2018

Another must to have lesson from Michigan Univeristy. After completing this lesson the Social Networks will be an analysis challenge.

교육 기관: Suyash D

Dec 19, 2018

An excellent course that provides a fair knowledge of social networks, the NetworkX package and how to work with networks in Python.

교육 기관: Henri

May 19, 2019

Great intro to networks; last assignment is challenging but is a good opportunity to put everything together (python+ML+Network).

교육 기관: Elias

Jan 11, 2018

This is a very informative course in the property of networks and the feature extraction you can obtain out of this. Excellent

교육 기관: Shiomar S C

Nov 05, 2019

Excelente course, the instructor really meks you undestand with the right structure and having meaningfull in video quizes

교육 기관: Dhananjai S

Jun 11, 2019

One of the best courses on social network analysis. Professor Daniel Romero did an excellent job explaining the contents.

교육 기관: Varga I K

Mar 09, 2019

It was great introducing the networks, but I found most of the assignments too straightforward except for the last weeks.

교육 기관: Mile D

Dec 20, 2017

Excellent explanations and examples. Recommended text to read was also very helpful. Thanks for providing this course!!!

교육 기관: Sarah H H

Jun 03, 2019

i found this course to be fun and straightforward. The assignments were directly aligned to instruction. Great course!

교육 기관: Christian P

Dec 29, 2019

Excellent, well taught and in-depth programming exercises. I really got my hands into programming with networkx here.

교육 기관: Oscar J O R

Oct 15, 2017

A really good course. Notebooks could be very useful to practice and maybe more exercises(not graded) with real data.