Math 527 Applied Linear Algebra (Graduate)
An application-focused approach to linear algebra in a variety of fields. Topics include matrices, gaussian elimination, vector spaces, determinants, inner products, orthogonality, least squares solution, eigenvalue problems, Gram-Schmidt process, matrix decomposition/factorization, Jordan canonical forms, methods of dimension reduction such as singular value decomposition or principal component analysis, quadratic forms, pseudo-inverses, Markov processes, data/image processing, and other advanced topics pertinent to data analysis. This course is perfect for high school math and science teachers wishing to extend their knowledge of linear algebra. Click here for syllabus.
Prerequisite Courses: Two semesters of calculus