Optimization
This course introduces the theory and practice of optimization. Both unconstrained and constrained problems are considered, as well as continuous and discrete optimization. Topics include linear programming, unconstrained optimization, constrained nonlinear optimization and integer programming. Applications to Statistics and Data Science will be explored. May not be held with the former MATH 3490.
Prerequisites & course information
PR/CR: A minimum grade of C is required unless otherwise indicated. Prerequisites: [one of MATH 2090 , MATH 2091 , MATH 2740 , the former MATH 2300, the former MATH 2301 , the former MATH 2350, or the former MATH 2352] and [one of MATH 2150 , MATH 2151 , MATH 2720 , MATH 2721 , or the former MATH 2750]; or consent of instructor. Mutually Exclusive: MATH 3490 Attributes: Mathematics Requirement, Science
Sources
- Course catalogue ↗2026-2027