— Scientific Computation

Prerequisites & course information

Course Description: Matrix-vector approach using MATLAB for floating-point arithmetic, error analysis, data interpolation, least squares data fitting, quadrature, zeros, optimization and matrix eigenvalues and singular values. Parallel computing for matrix operations and essential matrix factorizations. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Computer Science and Computer Science Engineering Majors only. Grade Mode: Letter. General Education: Science & Engineering (SE). Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One open to Computer Science and Computer Science Engineering Majors only. Grade Mode: Letter. General Education: Science & Engineering (SE).