Emphasis on the interplay between theory, application and numerical techniques. Review of vector spaces, complexity of algorithms and numerical techniques, applications of eigenvalues and eigenvectors. Singular value decomposition. Markov chains and probability matrices. Linear Transformations. Inner product spaces. Concepts will be illustrated through applications as chosen by the instructor. Lab work done with an appropriate software package.
Weekly Contact: Lab:1 hr. Lecture:3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1