Advanced topics in numerical analysis selected from iterative methods for linear systems, approximation of eigenvalues and eigenvectors, numerical methods for ordinary and partial differential equations, optimization methods and approximation theory, emphasizing error and convergence analysis and computer coding.
Prerequisite: MATH 340 with a “C” (2.0) or better; or graduate standing.
400-level Undergraduate Course available for Graduate Credit
