Foundations of Modern AI

Prerequisite: MATH 162 with a minimum grade of "C-" and (MATH 120 with a minimum grade of "C-" or MATH 202 with a minimum grade of "C-") This project-driven course examines the theory and practice of modern artificial intelligence. Students will learn to apply models to challenging problems and to evaluate model performance using benchmarks. The course also develops the mathematics underlying many AI methods, including probability, neural networks, gradient descent, the universal approximation theorem, transformer architectures, and attention mechanisms. Additional advanced topics will be selected by the instructor. Offered spring semester