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.
Applied Learning Project
Throughout the Specialization, you’ll apply advanced linear algebra concepts through readings, practice, and section-based problems. You’ll work with eigenvalues and eigenvectors, diagonalize matrices, analyze vector spaces, apply orthogonality and projection methods, represent linear transformations, and solve problems involving inner products, least squares, and optimization.
These activities will help you move from understanding advanced concepts to applying them across increasingly complex mathematical problems.
