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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

4.7
2,509件の評価
421件のレビュー

コースについて

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....

人気のレビュー

NK
2019年5月2日

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
2018年9月23日

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.

フィルター:

Applied Social Network Analysis in Python: 151 - 175 / 411 レビュー

by Rui

2017年10月11日

very good introductory course for social network analysis using Python.

by Diego F G L

2021年3月30日

Great course and and great contents. I really enjoyed the assignments.

by Dirisala S

2019年7月22日

The have lot of stuff to learn. It will definitely enhance your skill.

by Dibyendu C

2018年10月19日

Well structured and quality lecture content with excellent assignments

by Nikhil N

2021年7月18日

W​onderful course with very detailed explanations!!! Simply wonderful

by Liran Y

2018年5月20日

Interesting and fun. Daniel's lecturing style is clear and enjoyable.

by Chiau H L

2019年4月4日

Awesome course!!! Helped me a lot to get started with graph analysis

by Keqi L

2019年4月14日

Interesting slides and knowledge. e.g. Page rank is super cool!!!!

by Kai H

2018年11月8日

Good course, may be better if offer more practice and application.

by Tatek E

2020年3月23日

Excellent presentation, exercise and reading materials. Thank you

by wenzhu z

2018年2月22日

very clear logic, and will always wrap up at the end of the class

by 杨志陶

2020年5月17日

A practical way to learn social network analysis. Great course!

by Renzo B

2019年9月23日

I learned a lot of things that I can apply to my line of work.

by charles l

2019年2月4日

A completely new area for me, and a really fascinating course.

by Yee F

2021年7月1日

Course is much easier to understand that applied text mining.

by Haris P D

2020年1月31日

One of the most awesome course that I have taken on Coursera!

by Wai Y P S

2021年6月22日

Thanks you so much University of Michigan for Great course

by Marco Z

2020年4月22日

Very interesting , a new point of view for future analysis!

by Israel D D G

2020年8月22日

Excellent course, good technical and teoretical knowledge.

by LEE D D

2017年11月5日

Excellent! It was one of the great assignments I ever had!

by Manuel T

2018年1月30日

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

by Jiahui B

2017年11月28日

Very useful course. It helps me finish my course project.

by Ruihua G

2019年7月8日

this course provided a overview of the network analysis.

by Jiefei W

2020年4月11日

Practiced with what was covered in the 1th~3rd courses.

by Abdul N M

2019年3月12日

Gave me a very good understanding of the basic concepts