MATH-111(e): Linear Algebra

Lectures in this course (136)

Covers matrix notation for linear equations, solutions, and geometric interpretations.

Explores the polynomial q(t) = bt - 1² in a vector space context.

Explores linear transformations, matrices as functions, and geometric interpretations.

Explores linear algebra fundamentals, including key definitions, theorems, and practical applications in mathematics and technology.

Discusses properties of determinants, emphasizing the relationship between k and the determinant of matrix A.

Explores matrix operations, coefficients, multiplication properties, and the power of matrices.

Covers the concept of interesting subspaces related to matrices and the change of basis matrix.

Delves into matrix solutions with infinite possibilities for the equation Ax = Ac.

Covers linear dependence, independence, and applications in vector spaces.

Explores eigenvalues and eigenvectors in matrices through examples and calculations.

Covers matrix operations, coefficients, combinations, and applications in various scenarios.

Covers linear applications, matrices, injectivity, surjectivity, and matrix multiplication properties.

Explores the properties of linear transformations through step-by-step calculations and matrix manipulations.

Focuses on finding values for a matrix to be invertible.

Explores linear applications, associated matrices, and matrix operations in the context of injective and surjective maps.

Covers the process of row echelon form by performing various operations on matrices.

Introduces eigenvalues and eigenvectors for square matrices through examples.

Explores efficient determinant calculations using triangular matrices and specific row/column selections for simplification.

Explores characteristic polynomials, eigenvalues, and eigenvectors of matrices A, B, C, D, and E.

Explores symmetric matrices, diagonalization, and their real-world applications in data analysis.

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