AISE 3020A
0.50 credit · Main
This course explores the fundamental issues of fairness and bias in machine learning. In addition, the course explores many aspects of building ethical models while considering human bias and dataset awareness. Furthermore, the course will explore fundamental concepts involved in privacy and security of machine learning projects. Topics such as how to protect users from privacy violations while building useful transparent predictive models will be explored.
Data Science 3000A/B.
3 lecture hours/week, 2 lab hour/week.
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