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Learner Reviews & Feedback for Data Science Ethics by University of Michigan

4.8
stars
550 ratings
159 reviews

About the Course

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten." This course will help you answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair. Data scientists and anyone beginning to use or expand their use of data will benefit from this course. No particular previous knowledge needed....

Top reviews

LA
Jun 26, 2019

I really enjoyed the material and the way it was presented. Even though I am not new to the topic, still more avenues and perspectives were supported with very good examples. Very refreshing.

OA
Mar 9, 2021

The course was a great opportunity to understand more about the ethics behind the data science and even more, behind the technology. Some subjects will support me on the future researches.

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151 - 158 of 158 Reviews for Data Science Ethics

By Andrea M

Aug 25, 2020

It should be more complicated.

By Sivaranjani K

Jun 6, 2020

good

By Santosh k

May 27, 2020

Good

By Tangudu T

May 24, 2020

Good

By AKULA P

May 23, 2020

Good

By Brian W

Apr 14, 2021

This course is interesting, but not very complex. It does offer numerous case studies. You can explore pretty much the same material in a shorter period of time by reading "Weapons of Math Destruction" or "Calling Bulls&*t" which focus more on the specifics of how statistics and data science / machine learning can be either intentionally manipulated or inadvertently so. They cover p-hacking in more depth, visualizations that can be misleading, and many of the more deep ethical issues covered here.

By Peter P

Feb 17, 2018

The course provides a good insight into some of the issues with the ethics of data science. Perhaps there is too much focus on data validity and not enough on ethics. This course shows that there is a need for systematic ethical enquiry into this subject.

By sahithi k

Jul 6, 2020

good