This course provides an introduction to matrix computations, the study of algorithms for finding numerical solutions of linear algebra problems.
Majority of mathematical models cannot be solved exactly and have to be approximated. Most approximation techniques lead construction of a system of linear algebraic equations. These systems are usually large and have to be solved numerically. The study of their solution is fundamental for many branches of computational mathematics, from optimization to PDEs, statistics and data science.
Find exam info and full course description in the course catalogue.
To apply for the course you must either be enrolled in a bachelor's degree, have a bachelor's degree or have passed a qualifying entry examination.
Exchange Students: nomination from your home university
Freemovers: documentation for English Language proficiency
You can read more about the admission here.
Sergey Lapin is a professor in the Mathematics department at Washington State University. His research interest are Numerical modeling, scientific computing, mathematical biology, modeling of fluid flow. He has a Ph.D. in Applied Mathematics from University of Houston in 2005.