By their efforts in this course, students should improve in the following course learning outcomes: linear systems, vector spaces, linear transformations, augmented matrices, Gaussian reduction, vector equations, matrix equations, linear independence, affine geometry, subspaces, bases, coordinates, matrix operations, matrix inverses, elementary matrices, matrix factorizations, matrix representations, inner products, orthogonality, outer products, affine transformations, orthogonal projections, the Gram-Schmidt algorithm, least squares, determinants, Cramer's rule, cross products, eigenvalues, eigenvectors, characteristic polynomials, diagonalization, similarity
Additionally, students will improve in the following university Essential Learning Outcomes: Quantitative Literacy, Problem Solving, Communication, and Critical Thinking.