Data Science Ethics

Обучение бесплатное
Сертификация платная
1 час курса
О курсе

As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right away, without appreciating the possible consequences of their work.

This course focused on ethics specifically related to data science will provide you with the framework to analyze these concerns. This framework is based on ethics, which are shared values that help differentiate right from wrong. Ethics are not law, but they are usually the basis for laws.

Everyone, including data scientists, will benefit from this course. No previous knowledge is needed.

Data Science Ethics
Learn how to think through the ethics surrounding privacy, data sharing, and algorithmic decision-making.
Что Вы изучите?
  • Who owns data
  • How we value different aspects of privacy
  • How we get informed consent
  • What it means to be fair
H. V. Jagadish
H. V. Jagadish
Bernard A Galler Collegiate Professor, Electrical Engineering and Computer Science University of Mic...
H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan, and Distinguished Scientist at the Michigan Institute for Data Science. He is a Fellow of the ACM, serves on the Board of Directors of the Computing Research Association, and has previously served as a Trustee of the Very Large Database Endowment. He is winner of the 2013 Contributions Award from the ACM Special Interest Group on Management of Data (SIGMOD).
Эта платформа предоставляет все курсы бесплатно. Авторами выступают топовые университеты и корпорации, которые стараются удерживать стандарты качества. За несоблюдение дедлайнов, невыполнение домашнего задания студенты теряют баллы. Как и в других платформах, лекционные видео чередуются с практическими заданиями. Обучение проводится на английском, китайском, испанском, французском и хинди.