AMOD 574 - Computational Linear Algebra

Credits: 3
Credit Configuration: 2+2, 3 Cr.

A survey of computational applications of Linear Algebra (LA) designed to develop the ideas of linear algebra in a computational setting for solving science and engineering problems. Goals for this class include computational expertise, including applications to large datasets with: conversion of systems to matrices, row operations, inverses and determinants, eigenvalues, Gaussian elimination and matrix decomposition including singular value and QR decompositions. The idea of sparse vs. dense matrices and approximation will be explored. Other advanced topics related to data mining may be covered. This course will be taught primarily in Python or MATLAB.