The aim of this module is
to teach students how to derive, analyze and implement numerical methods for
solving systems of linear equations, computing eigenvalues of matrices,
approximating functions and integrals, solving differential equations. To
achieve these aims, students will numerically solve mathematical problems and
analyze the mathematical theory to build the methods used for the numerical
solution. The course will cover the basic topics of stability, error analysis
and efficiency for various numerical algorithms for solving linear systems, computing
eigenvalues, solving differential equations. Computer projects may be completed
using any preferred programming language. However, a numerical computing
environment known as Matlab will be used to teach the course, and Matlab codes will
be provided.
- Instructor: Bruno Carpentieri
- Instructor: Peter James Brannick
- Instructor: Jemma Prior
Coruse Syllabus: not available
- Instructor: Omar Lakkis
- Instructor: Tammam Tillo
- Instructor: Simone Ugolini
- Instructor: Vincenzo Del Fatto
- Instructor: Tahir Emre Kalayci
- Instructor: Fabio Persia
- Instructor: Nicolas Troquard
- Instructor: Syed Mehdi Abbas Rizvi
- Instructor: Tammam Tillo
Coruse Syllabus: not available
- Instructor: Evellin Cardoso
- Instructor: Benjamin Cogrel
- Instructor: Arif Ur Rahman
- Instructor: Marko Tkalcic
- Instructor: Mehdi Elahi
- Instructor: Markus Johann Gritsch
- Instructor: Francesco Ricci
- Instructor: Oliver Kutz
- Instructor: Ognjen Savkovic
The aim of this module is to present a rather comprehensive treatment of linear algebra and its applications. It covers vector and matrix theory to some degree of mathematical logic and rigor, emphasizing topics useful in other disciplines such as solving linear equations and computing determinants and eigenvalues of matrices. The course also provides practice in using linear algebra to think about problems in computer science, and in actually using linear algebra computations to address these problems.
- Instructor: Bruno Carpentieri