This course is designed to give engineering students in graduate level the expertise necessary to understand and use computational methods for the approximate/numerical solution of linear algebra problems that arise in many different fields of science like electrical networks, solid mechanics, signal analysis and optimisation. The emphasis is on methods for linear algebra problems such as solutions of linear systems, least squares problems and eigenvalue-eigenvector problems, the effect of roundoff on algorithms and the citeria for choosing the best algorithm for the mathematical structure of the problem under consideration.

Floating Point Computations. Vector and Matrix Norms. Direct Methods for The Solution of Linear Systems. Least Squares Problems. Eigenvalue Problems. Singular Value Decomposition. Iterative Methods for Linear Systems.