Lectures related to Linear Algebra: Matrix Representation of Linear Applications

Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.

Covers the organization of linear algebra course and exercises for civil engineering and environmental sciences students.

Covers fundamental linear algebra concepts like vector spaces and eigenvalues.

Showcases a non-diagonalizable matrix example and explores eigenvalues and eigenvectors.

Covers eigenvalues, eigenvectors, and characteristic polynomials in matrix transformations.

Covers eigenvectors, eigenvalues, and their significance in linear applications.

Explores eigenvalues and minimal polynomial, emphasizing their importance in linear algebra.