Courses

Vector spaces: basis and dimension, subspaces, space quotient, linear functions, isomorphisms of vector spaces, matrix of linear mapping and its rank. Diagonalization (eigenvalues, eigenvectors). Inner product spaces, orthogonal complement, Gram-Schmidt method, orthogonal, unary, symmetric, Hermitian, normal matrices.