Computer Science

Students study core computer graphics concepts, including the mathematical principles used for computer-generated imagery, shading, and light approximations. They also learn different geometry representations and modelling techniques and learn to apply what they have learned to practical computer graphics problems, using modern shader languages and graphics accelerators.

This course examines software engineering through programming with particular focus on the fundamentals of computing & programming. It includes building abstractions with procedures, data & objects; data modelling; and designing, coding & debugging programs of increasing complexity.

This course gives a general introduction to embedded system design which can be implemented using System-on-Chip technology. This kind of embedded systems contains both hardware and software components and therefore a hardware/software co-design is emphasized. The course gives a basic knowledge on specification methods, design representations (computational models) as well as related design methods. Special emphasis is placed on interface synthesis and low-power design methods.

This course builds up a toolbox of numerical optimization methods for building solutions in future studies, thereby making it an ideal supplement for students from many different fields in science. The course is taught both at a theoretical level that goes into deriving the math, and also on an implementation level with focus on computer science and good programming practice. Students participate in weekly programming exercises where they implement the algorithms and methods introduced from theory, and apply their own implementations to case-study problems like computing the motion of a robot hand or fitting a model to highly non-linear data. Topics include: first order optimality conditions, Karush-Kuhn-Tucker conditions, Taylors theorem, mean value theorem, nonlinear equation solving, linear search methods, trust region methods, linear least-squares fitting, regression problems, and normal equations.

This course examines database systems. It covers data models: entity-relationship, relational, object-oriented; relational database management systems: data definition, query languages, development tools; database application design and implementation; architecture of relational database management systems: storage management, query processing, transaction processing; lab: design and implementation of a database application.