MATH-275 Introductory Applied Linear Algebra
Geometry and algebra of vectors in Euclidean spaces, systems of linear equations, Gaussian elimination, Vector spaces, spanning sets, linear independence, subspaces, basis and dimension; matrices, algebra of matrices, the LU factorization, linear transformations, invertible matrices, determinants, eigenvectors and eigenvalues, orthogonality, the Gram-Schmidt process. Though basic theory of Linear Algebra will be covered, an emphasis will be given to techniques and applications of Linear Algebra to a set of areas such as Allocation of Resources, Linear Programming Problems, Markov Chains, Linear Economic Models, Population Growth, Least Squares, Data Fitting and Machine Learning.
Prerequisite
Student has completed all of the following course(s) MATH 166 - Calculus II