This course cover bias and fairness evaluation in artificial intelligence (AI) models. Bias is systematic differences in AI model performance among subgroups, leading to a higher failure rate against some groups. The course has a final project on the algorithmic bias. Students should have hands-on programming skills in machine/deep learning. Prerequisites: experience with machine learning and python programming.
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