Units: 4 Terms Offered: FaSpBasic and advanced fairness concepts and methods; applications to societal data for studying fairness and bias; fairness and bias effects in learning algorithms. Recommended Preparation: Knowledge of Python, linear algebra, probability, and statistics. Familiarity with artificial intelligence and machine learning. Instruction Mode: Lecture Grading Option: Letter
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