Jun 27, 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.
Mar 18, 2019
Absolutely delightful to have Professor Jagadish walking us through the course. The course was informative and very stimulating. Opens up to a new world of data science ethics. Thank you!
par Greg S•
Sep 01, 2018
Very relevant and interesting course. I recommend it.
par Menashe M•
Jun 12, 2018
Really liked the way the info was presented.
Oct 23, 2018
liked the case study at end of each topic
par Sergei K•
Dec 03, 2019
A must-take for anyone working with data
par Amitkumar H B•
Jul 05, 2018
Very much interactive and content ful
par PRANAV P K•
Apr 22, 2018
Best course for Data Science Ethics
par Olaf M•
Oct 01, 2019
Good, useful grounding in ethics.
par GOR B•
Dec 22, 2019
Great content, important topics
par Ramkumar I•
Apr 15, 2019
Crisp with lot of examples
par Nejde M•
Jan 07, 2020
par adriana s l e•
Feb 21, 2019
par Isabel H•
Mar 20, 2018
This is a good intro to the topic for data scientists with no prior background in ethics. As someone who has studied the philosophy of ethics (even if you've only taken one course in it) you'll likely be disappointed in the limited level of depth in terms of considering ethical theories. To be fair, the instructor does state this at the beginning of the course. My other issue I had with this course is that the assessment quizzes use true or false questions - which in my opinion represents a VAST simplification of the complexities of ethical questions. This kind of simplified black and white thinking is exactly what we do NOT want in the people creating and controlling our technology, so I was disappointed to see the assessment style encouraging it.
par Hillary S•
Sep 24, 2018
I really enjoy ethics courses and I liked that this related to something so ingrained in our daily lives: data. I think, in general, ethics lessons are undervalued so I am glad to see this one offered.
The professor was knowledgeable and did a good job. I would watch other courses with him teaching.
My only criticism would be that these ethics were mostly presented from one point of view. Ethics rules can be very subjective depending on who is applying them, so I think hearing from other professors as well as the one who taught it would be good.
par Reinhold L•
Nov 04, 2018
A good overview of privacy, ethics, informational consent etc.
The numerous case studies were very informative, relevant and helpful for the daily work in Data Science.
par Okindo I•
Aug 23, 2018
This is a good course, it is applicable to a wide range of fields.
I found it very helpful in my career.
Ethics is key in ever aspect of our life.
Mar 30, 2019
Great materials. Very original. But I think the lecturer needs to smile and put more energy in his talk. Hope you're having a good day!
par Dmytro I•
Mar 20, 2019
Good introductory course into the topic. Great lecturer. Think needs more deep dive into each topic with more diverse examples.
par Debra L T•
Jan 29, 2019
Presenter did not vary tone, was not engaging and made it very difficult to follow.
par Bea S•
Jan 22, 2020
I enjoyed taking this course because I have learned a lot.
par Codrin K•
Jul 02, 2018
Good overview of topics regarding ethics in data science.
par 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.
par Katherine S•
Jan 23, 2019
Good course. Challenging and thought provoking. The professor was very good, but, even if you complete all assignments, your certification and grade depends upon having others in the course go in and review your assignment. Even if you review more than you are required to review, if others don't review yours, you don't pass or get your certification. So, be aware of that if you are attending a class in the hopes of obtaining a certification. It is not guaranteed even if you do all of the work.