CS3390

In this course, we will explore the technical, social, and ethical ramifications of the choices we make at the different stages of the data analysis pipeline, from data collection and storage to understanding feedback loops in analysis. Through class discussions, case studies and exercises, students will learn the basics of ethical thinking in science, understand the history of ethical dilemmas in scientific work, and study the distinct challenges associated with ethics in modern data science.

Prerequisites: ("C-" or better in ((CS 1400 AND CS 1410) OR CS 1420) AND "B-" or better in CS 2420 AND "C" or better in MATH 1210 AND Major in Kahlert School of Computing) OR ("C-" or better in DS 2500 AND Data Science Certificate Status).

Fall and Spring