Contents: Linear systems - the Gaussian algorithm, matrices - LU decomposition, determinants, vector spaces, least squares - QR decomposition, linear maps, eigenvalue problem, normal forms - singular value decomposition; numerical aspects.

Systems of linear equations; matrix algebra, determinants; vector spaces, norms and scalar products; linear maps, basis transformations; eigenvalues and eigenvectors.

Linear Algebra:linear systems, vector calculus, matrix calculus, linear maps, orthogonal maps, trace & determinant, eigenvalues & eigenvectors, vector spacesstochastics:combinatorics, probability, probability densities, statistics