Learning

Eigenvalues, Eigenvectors, and Diagonalization: Theory and Applications

Linear Transformations and Matrix Representations → Applications to Geometric Transformations

This advanced university-level path guides learners from the fundamental concepts of eigenvalues and eigenvectors through the process of diagonalization, culminating in the spectral theorem and practical applications to linear systems and transformations. It emphasizes the underlying mathematical structure and the connections between algebraic and geometric perspectives.