Areas of Expertise
- Computable analysis
- Effective descriptive set theory
- Game theory and CS
Embedded systems are information processing systems embedded into enclosing products such as cars, telecommunication or fabrication equipment. They are essential for providing ubiquitous information, one of the key goals of modern information technology. The aim of this module is to provide an overview of embedded system design, to relate the most important topics in embedded system design to each other, and to obtain an appreciation of the model based approach to embedded systems design. The lab provides hands-on experience in the design of embedded systems, based on the Lego-Mindstorms kit. Awareness of logical concepts (propositional logic, first order logic) will help the understanding of this module. Due to the lab, the number of places available for this module is limited. Places will be allocated during the first week of teaching; the allocation criteria will be announced in the first lecture.
This course is an introductory course to the mathematical methods needed by a data scientist. It covers the basics of algebra, optimisation techniques, statistics, and Fourier analysis. The main goal of the class is for students to gain practical experience of the mathematical methods and tools that are essential in data science and that will be used in the other modules of this programme. The module is aimed at students with basic experience in mathematics.