CSC 340 - Scientific Computing
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.
Credit Hours: 3
Prerequisite Courses: CSC 231 with a minimum grade of C and MAT 162
Course Repeatability: Course may not be repeated. Maximum Repeatable Hours: 3
Click here for the Fall 2020 Class Schedule.