Methods in Scientific Computing

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The goal of the course is for you 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 you will learn the theoretical foundations, and develop practical skills through programming, and analysing the models, methods and algorithms.  

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

Link to the course homepage in Canvas (only for KTH students). 


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