Programme structure
In the Cybernetics and Autonomous Systems study option you will primarily select from the courses listed below, in addition to completing a 60 ECTS credit master project. There are four specialisations to choose from, however, by engaging with a supervisor early, you can customise and design your own course of study, aligning it with your interests and professional career aspirations.
Regardless of the chosen specialisation, the following core courses must constitute at least half of your coursework:
TEK4030 – Control of Manipulators and Mobile Robots (autumn)
TEK4040 – Mathematical Modelling of Dynamic Systems (autumn)
TEK4050 – Stochastic Systems (spring)
TEK4090 – Modern Control Systems and Cybernetics (autumn)
TEK5010 – Multi-Agent Systems (autumn)
TEK5020 – Pattern Recognition (autumn)
TEK5030 – Computer Vision (spring)
TEK5040 – Deep Learning for Autonomous Systems (autumn)
IN5590 – Rapid Prototyping of Robotic Systems (autumn)
These courses are indicated by an asterix (*) in the course lists for each specialisation below.
Alternative programme structure for students admitted before 2025.
You have the option to either take all courses during the first two semesters and focus on your master thesis in the final two semesters, or you can distribute the courses according to the following structure:
| 4th semester | Master Thesis | Master Thesis | Master Thesis |
| 3rd semester | Course | Master Thesis | Master thesis |
| 2nd semester | Course | Course | Master Thesis |
| 1st semester | Course | Course | Course |
| 10 ECTS credits | 10 ECTS credits | 10 ECTS credits |
Specialisations
1. Autonomous Systems
This specialisation focuses on the application of principles and technologies to develop and operate autonomous systems, emphasising hands-on experience with real-world robotic platforms used in industry and research. It will provide you with introduction to control systems and sensor technologies, while exploring machine learning and AI applications. Additionally, you will learn how to design, 3D print, and construct practical robotic systems.
Autumn courses:
Other relevant courses:
TEK5020 – Pattern Recognition*
TEK5070 – Wireless communications for autonomous and critical sensor systems
IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
Spring courses:
TEK5030 – Computer Vision*
TEK5600 – Visualization of Scientific Data
IN4050 – Introduction to Artificial Intelligence and Machine Learning
Other relevant courses:
IN4140 – Introduction to Robotics (autumn)
2. Control and Cybernetics
This specialisation offers an in-depth exploration of both the theoretical and practical aspects of managing dynamic systems. You will gain a solid foundation in developing control strategies for manipulators, mobile robots and multi-agent systems. In addition, you can widen your perspective and take application-oriented courses in energy and/or space systems.
Autumn courses:
Other relevant courses:
TEK5020 – Pattern Recognition*
TEK5040 – Deep Learning for Autonomous Systems*
TEK5070 – Wireless communications for autonomous and critical sensor systems
IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
Spring courses:
TEK4050 – Stochastic Systems* (Strongly recommended)
TEK5600 – Visualization of Scientific Data
Other relevant courses:
TEK5030 – Computer Vision*
IN4050 – Introduction to Artificial Intelligence and Machine Learning
IN4140 – Introduction to Robotics
3. Detection and sensing
This specialisation equips you with advanced skills and knowledge in the detection, analysis, and interpretation of data from a wide range of different sensor systems. You will engage with both hardware and software aspects of sensing, working with traditional computer vision algorithms and cutting-edge machine learning techniques.
Autumn courses:
Other relevant courses:
TEK4090 – Modern Control Systems and Cybernetics*
TEK4010 – Optics and Light
TEK5070 – Wireless communications for autonomous and critical sensor systems
IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
Spring courses:
TEK5030 – Computer Vision* (Strongly recommended)
TEK5050 – Imaging and Detection of Optical and Infrared Radiation
TEK5600 – Visualization of Scientific Data
Other relevant courses:
TEK4050 – Stochastic Systems*
IN4050 – Introduction to Artificial Intelligence and Machine Learning
IN4140 – Introduction to Robotics
4. Medical technology
In this specialisation, you will explore the intersection of engineering, medicine and technology. Through hands-on projects and coursework, you'll work with tools and techniques to develop devices and systems that enhance patient care and medical processes. This knowledge can be applied to various healthcare settings, contributing to advancements in treatment, patient monitoring, and preventive care, ultimately aiming to improve health outcomes and quality of life.
Autumn courses:
TEK4030 – Control of Manipulators and Mobile Robots*
Other relevant courses:
TEK4040 – Mathematical Modelling of Dynamic Systems*
TEK4090 – Modern Control Systems and Cybernetics*
IN4015 – Ultrasound Imaging
IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
FYS4250 – Biomedical Instrumentation
FYS4239 – Electrical Bioimpedance
Spring courses:
TEK5030 – Computer Vision*
TEK5600 – Visualization of Scientific Data
Other relevant courses:
TEK4050 – Stochastic Systems*
IN5050 – Programming heterogeneous multi-core architectures
IN4050 – Introduction to Artificial Intelligence and Machine Learning
IN4310 – Deep Learning for Image Analysis
FYS4240 – Data Acquisition and Control
FYS4239 – Electrical Bioimpedance
Diploma and degree
This programme leads to the following degree: Master of Science in Informatics: robotics and intelligent systems