What is intelligent behaviour? How do computers recognize faces and objects? In this programme, you will learn how to design and implement intelligent systems.
This Master's programme has a selection procedure. The application deadline is 1 May 2024. For more information about the selection procedure, please check here .
These technologically advanced systems can perceive and respond to the world around them. Intelligent systems can take many forms, from facial recognition at security checks to automated vacuums and OpenAI's DALL-E that generate digital images from natural language descriptions. The Master's programme in Artificial Intelligence is made up of three core topics, reflected in three specializations: Computational Learning, Multi-Agent Systems, and Robotics.
Computational Learning
Automated translation between languages, face recognition, automated satellite image processing, or self-driving cars are all based on 'intelligent' computer algorithms. These algorithms are based on insights obtained in the cognitive and neurosciences on the one hand and are guided by fundamental principles of statistics, formal logic and dynamical systems theory on the other hand.
The courses taught in this specialization cover cornerstone
topics of this interdisciplinary field, including machine learning,
artificial neural networks and pattern recognition.
Robotics
A robot taking samples and collecting information on the moon is an example of an autonomous system. It operates and carries out missions independently. Regardless of its surroundings, it responds with a certain intelligence. While traditional AI focuses on cognition and reasoning as isolated abilities, we strongly believe in perception as an active behaviour, which is integrated into general cognition.
The courses taught in the
area of cognitive robotics are related to research in
social/domestic robotics, human-robot interaction, and how robots
can extend their knowledge over time by interacting with non-expert
users.
Multi-Agent Systems
When a team of robots play football they have to communicate
and cooperate with each other. This is an example of multiple
agents acting concurrently; a multi-agent system. When designing
these systems, techniques from computing science and logic are
combined with knowledge about the interaction amongst humans and
animals.
Read moreI have the opportunity to take courses about specific topics that interest me, but I also get to go outside of my comfort zone if I want to.
Isabelle Tilleman - Student of the MSc Artificial Intelligence
I did the Bachelor Artificial Intelligence at the University of Groningen. I really liked my Bachelor's degree, so I felt like this Master's degree would be perfect for me. I am officially in the Computational Intelligence track, but I am also taking the courses in the Multi-Agent Systems track.
The programme is what I hoped it would be. Courses are more project-oriented and are more in-depth. I have the opportunity to take courses about specific topics that interest me, but I also get to go outside of my comfort zone if I want to. In both cases, the work is even more rewarding than it was in the Bachelor's degree.
My favourite part of the programme so far has been that there are fewer students in each class. This allows for a better connection with the teachers and more interactive classes, which is very engaging.
I am currently working on my Master's thesis on knowledge transfer in energy regulation systems with TNO. This allows me to get an idea of what life is like outside of the university while finishing up my studies at the same time. I am not sure yet what I will do after my studies, but only because there are so many exciting options!
Read moreHow humans learn new tasks
After doing her master's project in the USA, Trudy wanted to continue to work on the edge of knowledge. She ended up back in Groningen for a PhD project about the transfer of cognitive skills. She builds computer models which show how humans learn new tasks and tests them by comparing them to, for example, test scores or brain activity. Using her models we can learn more about how your brain uses what you already know to learn something new.
