Linear Algebra for Data Analysis

Catalog description

In this computer science course students use a high-level programming language as a vehicle to discuss those aspects of linear algebra that are most important in data analytics. Students develop intuition and an understanding of how to use linear algebra, rather than on proofs. The main topics include basic matrix operations, linear transformations, ranges, linear combinations and spans, systems of linear equations, symmetric matrices, inverses, determinants, triangular matrices, trace, eigenvalues and eigenvectors.