Linear Algebra

Advanced Courses

Linear Algebra

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Course Topics:

Course Topics are organized as six modules with five granular topics covered under each module. Click through below to see all modules/topics for this course.

Introduction to Vector Spaces

Includes definition of a vector space, subspaces, spans, linear independence, and basis/dimension.

Linear Maps

Includes maps, nullspace/kernel, injective/surjective/bijective spaces, isomorphisms, matrices, rank nullity, and product/quotient spaces.

Eigenvalues and Eigenvectors

Includes eigenvalues, eigenvectors, characteristic polynomials, invariant subspaces, upper triangular matrices, eigenspaces, and diagonalization.

Inner Product Spaces

Includes generalized Cauchy-Schwarz inequalities, orthonormal bases, Gram-Schmidt process, and orthonormal complements.

Operators over Vector Spaces

Includes adjoint operators, normal operators, the Spectral Theorem, positive operators, isometries, and singular value decomposition.

Trace, Determinants, and other applications

Relates trace and determinant to the previous, more abstract ideas, to tie together loose ends.

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