Prerequisites: MATH 206A, MATH 207B; graduate standing; or consent of instructor
Description: Introduces stochastic optimization and standard numerical methods to approximate solutions to stochastic ordinary differential equations and stochastic partial differential equations. Investigates consistency, stability, and convergence of numerical methods. Also investigates convergence, rate of convergence, and its connection with stochastic differential equations. Includes applications and implementation of stochastic methods.