学生对 密歇根大学 提供的 Applied Social Network Analysis in Python 的评价和反馈
课程概述
热门审阅
NK
May 2, 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 23, 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.
401 - Applied Social Network Analysis in Python 的 425 个评论（共 427 个）
创建者 Nicolas B
•Oct 6, 2017
Very good Course.
创建者 THABSHEER H
•Oct 16, 2020
nicely explained
创建者 arpit m
•Dec 15, 2018
very good course
创建者 Raghunath P
•Nov 10, 2018
Great Course!
创建者 Vinit D
•Jan 16, 2020
Tough course
创建者 Avi R
•Aug 3, 2019
Satisfactory
创建者 Jean E K
•May 18, 2018
good teacher
创建者 TEJASWI S
•Aug 2, 2019
Good course
创建者 Andreas C
•Dec 2, 2017
quite good
创建者 Chethan S L
•Oct 2, 2019
Excellent
创建者 Xing W
•Dec 3, 2017
Not bad
创建者 shubham z
•Jun 13, 2020
good
创建者 Mallikarjuna R Y
•May 5, 2020
good
创建者 V B
•Dec 30, 2020
NA
创建者 Alexandra C
•Feb 28, 2021
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
创建者 Daniel B
•Dec 18, 2020
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 On top of that, the course uses the outdated networkx 1.11, while 2.0 has been out for over three years.
创建者 Jeremy .
•Jan 1, 2021
Some of the assignment organization could have been better, but otherwise the information was rock solid!
创建者 Jenny z
•Dec 1, 2020
better if TA could prepare projects with updated versions of libraries
创建者 József V
•May 4, 2018
Useful but weaker comparing to Pandas or Scikit courses.
创建者 Sara C
•May 16, 2018
i like the way that lecturer teach.
创建者 Leon V
•Oct 8, 2017
it was okay, 3.5 really
创建者 DW J
•Apr 6, 2018
hm..
创建者 Afreen F
•Feb 7, 2021
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.
创建者 MENAGE
•Feb 22, 2021
Aimerais avoir plus de temps et de conseils pour bien réussir..
创建者 Natasha D
•Dec 5, 2019
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.
Coursera Footer
