Explore the moral, social, ethical, and legal ramifications of the choices made at the different stages of the data analysis pipeline, from data collection and storage to analysis and use. Students will learn the basics of ethical thinking in data science, understand the history of ethical dilemmas in scientific work, study issues of fairness, transparency, and algorithmic bias associated with machine learning, and explore the distinct challenges associated with ethics and privacy in modern data science.
Gopher Grades is maintained by Social Coding with data from Summer 2017 to Summer 2025 provided by the University in response to a public records request