Description: Introduction to the design, application, and performance of numerical algorithms fundamental to scientific computation. Topics may include error and error propagation; matrix applications such as finding solutions to linear systems, finding eigenvalues and eigenvectors, or finding linear principal components; optimization; basic Markov modeling; Fourier processing; and curve fitting. Emphasizes relative merits and implementations of algorithms.