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学生对 加州大学戴维斯分校 提供的 Computational Social Science Methods 的评价和反馈

4.8
18 个评分
4 条评论

课程概述

This course gives you an overview of the current opportunities and the omnipresent reach of computational social science. The results are all around us, every day, reaching from the services provided by the world’s most valuable companies, over the hidden influence of governmental agencies, to the power of social and political movements. All of them study human behavior in order to shape it. In short, all of them do social science by computational means. In this course we answer three questions: I. Why Computational Social Science (CSS) now? II. What does CSS cover? III. What are examples of CSS? In this last part, we take a bird’s-eye view on four main applications of CSS. First, Prof. Blumenstock from UC Berkeley discusses how we can gain insights by studying the massive digital footprint left behind today’s social interactions, especially to foster international development. Second, Prof. Shelton from UC Riverside introduces us to the world of machine learning, including the basic concepts behind this current driver of much of today's computational landscape. Prof. Fowler, from UC San Diego introduces us to the power of social networks, and finally, Prof. Smaldino, from UC Merced, explains how computer simulation help us to untangle some of the mysteries of social emergence....
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1 - Computational Social Science Methods 的 4 个评论(共 4 个)

创建者 Muxin L

Mar 23, 2020

Great introduction to the specialization series on computational social science. Some technical tools are introduced but the course is largely a primer to what's currently possible in the digital age. Recommend for anyone curious about what this discipline is.

创建者 Sukanto M

Feb 24, 2020

A much needed course in the current scenario.

创建者 Benjamin P

Mar 02, 2020

Excellent introduction!!!!

创建者 Noor Q

Mar 07, 2020

This is a really fun course, even though I had some knowledge in the topic it is presented in a fun creative way that I learned a lot and never felt bored.

There were few issues though, the peer graded assessment asks for 5 pictures and then awards people who post more than 5 without saying that is the case in the instructions, as a teacher myself I would never expect students to provide more than they are asked for and penalize them if they don't.

I also found some of the machine learning lecture in week 3 confusing, especially considering I had some background which made me able to keep up, others might struggle.