Numerical Linear Algebra
Official Course Description
The main goal of the course is to give an introduction to numerical linear algebra. The course treats numerical methods and principles for solving fundamental problems in linear algebra. The course prepares for further studies in numerical analysis, statistics, computer science and image analysis. Furthermore, the students' ability to solve problems and implement numerical methods in code is trained.
The course covers:
- Direct and/or iterative solution methods for various linear algebra problems such as linear systems of equations, eigenvalue problems and the least-squares method,
- Matrix and vector norms, orthogonalisation, projection, matrix factorisations, direct and iterative solvers, condition numbers, stability of a method, complexity of an algorithm,
- Applying these concepts to construct numerical methods and solve problems in linear algebra,
- The significance of important matrix classes in numerical linear algebra.
For admission to the course, students must meet the general entry requirements for higher education, English 6 and 60 higher education credits in science including knowledge equivalent to the courses MATA21 Analysis in One Variable, 15 credits, NUMA01 Computational Programming with Python, 7.5 credits, MATA22 Linear Algebra 1 7.5 credits, and MATB22 Linear Algebra 2, 7.5 credits are required.