Chevron Left
返回到 Applied Social Network Analysis in Python

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

4.6
2,631 个评分

课程概述

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....

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.

筛选依据:

1 - Applied Social Network Analysis in Python 的 25 个评论(共 435 个)

创建者 Mark G

Apr 19, 2020

创建者 Aziz J

Dec 28, 2017

创建者 Oliverio J S J

Feb 25, 2018

创建者 Luis d l O

Mar 2, 2018

创建者 Ryan D

Aug 10, 2019

创建者 Kevin c

Aug 14, 2019

创建者 XU D

Oct 13, 2017

创建者 David M

Nov 15, 2018

创建者 Siddharth S

Jun 14, 2018

创建者 Philipp A R

Apr 7, 2020

创建者 Jingting L

Sep 24, 2018

创建者 Christos G

Sep 18, 2017

创建者 Brian L

Apr 17, 2018

创建者 Wei W

Dec 9, 2018

创建者 Daniel W

Feb 19, 2019

创建者 Cathryn S

Sep 12, 2020

创建者 Juha S

Feb 21, 2021

创建者 Mark H

Feb 7, 2018

创建者 Ahmad H S

Aug 5, 2019

创建者 Hiroki T

Mar 26, 2021

创建者 A P

Jul 5, 2021

创建者 Eric S

Oct 28, 2018

创建者 Christopher S

May 8, 2021

创建者 TAN J Y

Jun 4, 2020

创建者 David P

Feb 7, 2022