Error theory. Solution of linear systems: conditioning, Gauss' method and pivoting, matrix factorization: LU and Cholsky; applications. Eigenvalues: power method and extensions, similarity transformations, Householder transformation; QR factorization; reduction to Hessenberg and tridiagonal forms, QR method. Approximation of functions: discrete least-squares: solution by means of normal equations. Singular Value Decomposition and application to the least-squaresproblem. Numerical solution of differential equations by means one step and multistep methods.

Laboratory: 5 exercises about topics addressed during the semester (the use of Matlab is required)