Modern Artificial Intelligence and Machine Learning

4 credits

Provides a broad introduction to modern methods and implementations in artificial intelligence and machine learning. Covers a range of problems and approaches such as regression, gradient descent, classification, ensemble methods, graphical models, reinforcement learning, and neural networks. Includes analysis of bias and fairness in artificial intelligence methods. Recommended: familiarity with a coding language such as Python; introductory statistics; introductory calculus; and linear algebra. Offered: A.