Background in Linear Algebra: subspaces, ranks, vector, and matrix norms. Perturbation theory for linear systems and eigenvalue problems. Solution methods of linear systems and least-squares problems. Matrix factorizations. Computation of eigenvalues/eigenvectors. Singular value decomposition. Matlab and/or Python/numpy for demonstrating algorithms. Introduction to sparse matrix methods.
prereq: csci2033 or math2142 or math2243 or math2373 or math4242
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