MATH-111(c): Linear Algebra

Lectures in this course (59)

Introduces symmetric and anti-symmetric matrices, matrix powers, inverses, elementary matrices, and matrix manipulation.

Covers the concept of basis, linear transformations, matrices, inverses, determinants, and bijective transformations.

Explores the theory and applications of matrix determinants, emphasizing their role in matrix invertibility and solution uniqueness.

Covers matrix operations and properties of matrices, including symmetric and anti-symmetric matrices.

Covers the concept of inverse matrices and systems resolution, including the conditions for matrix invertibility and the Gauss-Jordan algorithm.

Explores upper triangular block matrices, invertibility, elementary transformations, and determinants with examples.

Explores linear combinations, spans, and matrix equations to determine solution sets.

Covers elementary matrices, matrix factorization, and LU decomposition.

Explores matrix determinant properties, quick calculations, and geometric interpretation in vector spaces.

Covers the algorithm for matrix decomposition and base change in linear algebra.

Covers the definitions and properties of vector spaces, including axioms and examples.

Explains kernel, image, and linear maps, illustrating concepts with examples.

Explores the Rank Theorem in linear algebra, covering matrix properties and determinants.

Explores multilinear groin and determinants, including the Sarrus rule and proof by induction.

Covers the basics of linear mapping and coordinate systems.

Explores linear mapping, isomorphism, and change of bases in vector spaces.

Explores determinants, similarity invariance, Cramer's formula, and geometric interpretations in matrices.

Explains cofactors, eigenvectors, eigenvalues, and studying linear applications.

Covers the concept of dimension in a vector space and bases.

Explores matrices, change of bases, eigenvectors, eigenvalues, and vector spaces.

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