Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.
コロラド大学ボルダー校（University of Colorado Boulder）
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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ETHICAL ISSUES IN DATA SCIENCE からの人気レビュー
The only reason to not give 5 stars is the need for an audit option where i can learn the concepts without needing to turn in assignments - i'm not looking for a grade. But the course is awesome!
A course full of valuable information and beautiful skills Thank you so much I hope to be with you in other courses
This is an awesome general overview on the ethical issues we are likely to run into as data scientits and researchers.
I learned a lot about ethical issues and computer Science. Good lectures, good reading material, but a whole lot of writing
Vital Skills for Data Science専門講座について
Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data. They will be introduced to the ethical questions every data scientist should be aware of when doing an analysis. The field of cybersecurity makes the data scientist aware of how to protect their data from loss.