📖Program Curriculum
The master's programme runs for a duration of two years, leading to a Master of Science (MSc) degree. During each year, students can earn 60 credits (ECTS) and complete the programme by accumulating a total of 120 credits. Credits are earned by completing courses where each course is usually 7.5 credits. The programme consists of compulsory courses, compulsory elective courses and elective courses.
Compulsory courses year 1
During the first year, the master's programme starts with four compulsory courses that form a common foundation in Systems, control and mechatronics. Each course is usually 7.5 credits.
Modelling and simulation
Discrete event systems
Linear control system design
Model-based development of cyber-physical systems
Compulsory courses year 2
In the second year, you must complete a master's thesis in order to graduate. The thesis may be worth 30 credits.
In Design project in systems, control and mechatronics, you will solve a larger design and implementation problem in a team where the skills from the previous courses are necessary to successfully solve the project.
Design project in systems, control and mechatronics
Master’s thesis
Compulsory elective courses
Through compulsory elective courses, you can then specialize in various subjects. During years 1 and 2, you need to select at least three compulsory elective courses out of the following in order to graduate.
Constraint programming and applied optimization
Robust and nonlinear control
Nonlinear optimisation
Simulation of production systems
Applied signal processing
Modelling and control of mechatronic systems
Model predictive control
Discrete optimisation
Linear and integer optimisation with applications
Learning dynamical systems using system identification
Sensor fusion and nonlinear filtering
Elective courses
You will also be able to select courses outside of your programme plan. These are called elective courses. You can choose from a wide range of elective courses, including the following:
Deep machine learning
Computer vision
Decision-making for autonomous systems
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