Vector spaces: basis and dimension, subspaces, quotient spaces, linear mappings, vector space isomorphisms, matrix of a linear mapping and rank. Diagonalization (eigenvalues and eigenvectors). Inner-product spaces, orthogonal complement, Gram-Schmidt process, orthogonal, unitary, symmetric, hermitian, normal transformations. Matrix decompositions (LU, QR).