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学生对 密歇根大学 提供的 Applied Social Network Analysis in Python 的评价和反馈

2,569 个评分


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....



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.


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.


151 - Applied Social Network Analysis in Python 的 175 个评论(共 427 个)

创建者 Vighneshbalaji

Apr 28, 2020

Very Useful. I learned a lot. Thanks to Coursera and University of Michigan

创建者 Chanaka S

Aug 1, 2020

Lecture is God To Me The Person Who has Good Knowledge then easy to study

创建者 Amila R

Sep 30, 2019

Good starting point for those who want ro learn social network analysis.

创建者 Roberto L L

Mar 26, 2019

It was a wonderful course, linked network's models and machine learning.

创建者 高宇

Dec 2, 2018

Very Nice Coursera! It lead me to reknow the relations among the worrld.

创建者 Thaweedet

Aug 15, 2018

Great, You will to learn how to develop feature for social network data

创建者 Mischa L

Jan 6, 2018

Great course. Very good homework assignments, but somewhat on easy side

创建者 Rui

Oct 11, 2017

very good introductory course for social network analysis using Python.

创建者 Diego F G L

Mar 30, 2021

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

创建者 Dirisala S

Jul 22, 2019

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

创建者 Dibyendu C

Oct 19, 2018

Well structured and quality lecture content with excellent assignments

创建者 Nikhil N

Jul 18, 2021

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

创建者 Liran Y

May 20, 2018

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

创建者 Namrata T

Mar 24, 2022

Terrific Course. Learned a lot in graph theory and network analysis.

创建者 Chiau H L

Apr 4, 2019

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

创建者 BCN R

Jul 30, 2022

great course and specialization! quality of the contents is superb

创建者 Keqi L

Apr 14, 2019

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

创建者 Kai H

Nov 8, 2018

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

创建者 Tatek E

Mar 23, 2020

Excellent presentation, exercise and reading materials. Thank you

创建者 wenzhu z

Feb 22, 2018

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

创建者 杨志陶

May 17, 2020

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

创建者 Renzo B

Sep 23, 2019

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

创建者 Charles L

Feb 4, 2019

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

创建者 Yee F

Jul 1, 2021

Course is much easier to understand that applied text mining.

创建者 Haris P D

Jan 31, 2020

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