Chevron Left
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
2,442件の評価
409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: 376 - 398 / 398 レビュー

by Andreas C

2017年12月2日

quite good

by Chethan S L

2019年10月2日

Excellent

by Xing W

2017年12月3日

Not bad

by shubham z

2020年6月13日

good

by Mallikarjuna R Y

2020年5月5日

good

by V B

2020年12月30日

NA

by Mark H

2018年2月7日

I liked the lecturer and the tempo of the lectures, but this course felt a little light compared to the others in the specialization. The quizes were also good. But for me the course was a bit off topic. Given that, the various skills I learned in the other courses did come together in the final programming assignment. As a stand alone course I would give it four stars, but it gets three because it's required for the data science specialization.

by Siddharth S

2018年6月14日

The Course Deserves 5 Stars BUTThe fundamental flaw that felt absent in the last two courses of the specialisation was the in lecture Jupyter Notebook Demonstrations, it really helped the students feel in sync with the mentors.Please correct the same all the 5 courses of this specialisation deserve 5 starts :)

by Alexandra C

2021年2月28日

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

2020年12月18日

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 Jeremy .

2021年1月1日

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

by Jenny z

2020年12月1日

better if TA could prepare projects with updated versions of libraries

by József V

2018年5月4日

Useful but weaker comparing to Pandas or Scikit courses.

by Sara C

2018年5月16日

i like the way that lecturer teach.

by Leon V

2017年10月8日

it was okay, 3.5 really

by DAWUN J

2018年4月6日

hm..

by Afreen F

2021年2月7日

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

2021年2月22日

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

by Natasha D

2019年12月5日

The lectures and first three assignment are extremely superficial. Mostly they throw a bunch of definitions of metrics at you, give you some one-liners that will calculate specific metrics, then ask you to spit back those one liners (essentially no discussion of applications, etc). Then the fourth and final assignment is an interesting application of what you've learned but the grader is a NIGHTMARE. It is super buggy and your true task is to learn how the grader works, not how to write code and apply what you've learned about data science. I would not recommend this course unless you need it to finish the specialization.

by Hiroki T

2021年3月26日

Python and related libs are SUPER old. Some important codes used in this specialization were duplicated and you cannot get enough explanations even on Google. Moreover, auto-graders have lots of problems. I finished this specialization but I cannot recommend this.

by Moustafa S

2020年8月19日

not usefull course, out dated materials and it doesn't work on new library, what's the use of it if it doesn't work anymore and noone uses it?

by Christopher S

2021年5月8日

Vague, little explanation, I can get a better education on Udemy

by Sonam A

2019年12月18日

not interesting.