The goal of the course is for the student to develop an understanding of general and efficient numerical methods and algorithms, and their role in fundamental models of computational science, such as artificial neural networks, particle systems, ordinary differential equations and partial differential equations. Research challenges in the field are highlighted, for example with respect to parallel and distributed computing.

In the course the student will learn the theoretical foundations, and develop practical skills through programming and analysing the methods, algorithms and models.

This course is mandatory for the Scientific Computing track (CSSC) of the Master's programme in Computer Science.