COURSE CURRICULUM

The Master's Research Paper option requires students to complete six courses, each with a 0.50 unit weight, selected from two lists, with at least four courses taken from List A. A maximum of two courses can be those predominantly taken by undergraduate students. List A core courses include foundational subjects such as CM 730/CS 687 Introduction to Symbolic Computation, optimization courses like CM 740/CO 602/CS 795 Fundamentals of Optimization or CO 666 Continuous Optimization, numerical analysis courses such as CM 750/AMATH 741/CS 778 Numerical Solution of Partial Differential Equations, computational inference and statistical learning courses including CM 761/STAT 840 Computational Inference and related options, and CM 770/AMATH 740/CS 770 Numerical Analysis. List B offers a broad selection of advanced topics spanning applied mathematics, optimization, quantum information, computer science, and statistics, including courses like AMATH 655 Control Theory, CO 650 Combinatorial Optimization, CO 681 Quantum Information Processing, CS 680 Introduction to Machine Learning, and STAT 940 Deep Learning, among many others. The program is designed to provide a comprehensive and flexible curriculum that prepares students for advanced research and careers at the intersection of computational mathematics, optimization, and data science, with opportunities to tailor their studies based on interests and career goals.