Numerical Methods

Undergraduate

Survey of computational methods and algorithms; basic concepts (algorithm, computational cost, convergence, stability); roots of functions; linear systems; numerical integration and differentiation; Runge-Kutta method for ordinary differential equations; finite-difference method for partial differential equations; fast Fourier transform; Monte Carlo methods. Implementation of numerical algorithms in a scientific programming language. Course Format: Lectures, 3 hours per week; lab, 1 hour per week. Prerequisite(s): MATH 1P02 or MATH 1P06; MATH 1P11 or MATH 1P12; MATH 2P12 or permission of the instructor Course Notes: This course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.