To improve the analytic skills to the level required for engineering and financial applications.
To develop the students' abilities needed for problem solving in linear algebra.
- Understanding of the principles of linear algebra and its application in ML/AI, engineering and finance.
- Introduction to transforms and their use in image processing, engineering and probability/statistics.
- Introduction to functions of several variables and optimisation.
- Eigenvalues, eigenvectors and their generalisation
- Jordan form
- Singular value decomposition, with applications
- LU and QR decompositions
- Spectral Decomposition
- Least Squares Method
- Cholesky factorisation, with applications
- Iterative methods for solving linear systems
- Vector and matrix norms and condition numbers
- Metric spaces and convergence, application to linear equation solvers
- Laplace and Fourier transforms, with applications
- Functions of several variables
- Method of conjugate gradients and its role in optimisation
Lectures and small group tutorials.
Examination and approximately 7 small, regular courseworks.
Module leadersProfessor Abbas Edalat
Professor Peter Harrison