Take your linear algebra skills further by exploring the structures and methods that connect vectors, transformations, orthogonality, and optimization.

In this Specialization, you’ll build on foundational linear algebra concepts as you study eigenvalues and eigenvectors, vector spaces, orthogonality, linear transformations, and inner product spaces. You’ll also work with advanced methods including matrix diagonalization, the Gram–Schmidt process, QR factorization, singular value decomposition, least squares regression, quadratic forms, and constrained optimization. Through guided practice and problem solving, you’ll strengthen your ability to analyze and represent relationships across more advanced linear algebra settings. This course is part of the Advanced Topics in Linear Algebra and Applications Specialization and can also be taken independently.