MTH 308 Computational Linear Algebra

A course in the techniques and applications of linear algebra in the field of data science. The core topics include solving systems of linear equations, eigenvalues and eigenvectors, matrix decomposition, the pseudoinverse and least squares approximations, and the singular value decomposition. Theory is supplemented with extensive applications and computer programming.
Credits: 4
Prerequisite: MTH 243Z or MTH 365 with a grade of C- or better, and CS 133 or CS 161 with a grade of C or better, or consent of instructor

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