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.