MATH 31246

About this course

An introductory course in linear algebra emphasizing both mathematical foundations and computational practice. Topics include vector operations and geometry, norms, linear systems and Gaussian elimination, linear independence, bases, orthogonalization, matrix factorizations (LU, QR, SVD), eigenvalue decomposition, determinants, rank, and inverses. Students implement and visualize these concepts in Python through hands-on labs and modules. Applications from data science, machine learning, image processing, dynamical systems, and network analysis motivate the theory throughout.