(Lab required) 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. Prerequisites: (one of MATH 2090, MATH 2091, 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).Hide course graph
Winter 2020 section
Instructor: Shaun Lui CRN: 58360 Lecture Location: TBA Dates: January 06 – April 07 Time: 10:30–11:20, M.W.F. Tutorial Location: TBA Dates: January 06 – April 07 Time: 13:30–14:20, W.