Artificial Intelligence

What is intelligent behaviour? How do computers recognize faces and objects? In this programme, you will learn how to design and implement intelligent systems.

The Master's programme in Artificial Intelligence is made up of five core topics, reflected in the specializations: Machine Learning, Multi-Agent Systems, Robotics, AI Engineering and Hybrid Intelligence. There is also the possibility to follow a Science, Business and Policy Track.

Machine 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 computational social choice, argumentation between agents, collective intelligence, computational game theory, and dynamic epistemic logics for intelligent interaction.

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.

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.

Hybrid Intelligence
The specialization Hybrid Intelligence deals with designing systems where humans, agents, robots and/or other AI systems work together as a team. Students will learn to increase transparency and help teams to achieve their goals under uncertainty and inaccuracy. These factors have their own profound influence on the interaction in hybrid teams.

The courses taught in the area of hybrid intelligence are centered around trustworthy and explainable AI, human-centered AI, and human-robot interaction.

AI Engineering
From web platforms that provide personalized recommendations based on your viewing habits—such as Netflix, YouTube, and Spotify—to intelligent assistants like Siri and Watson, the skills of AI engineers also encompass cyber-physical systems, including self-driving cars developed by Waymo.
The courses offered in the AI Engineering specialization provide a solid understanding of the entire AI and machine learning development process, enabling students to design, build, and manage AI-powered software that is reproducible, testable, and adaptable to future advancements

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Artificial Intelligence

Science, Business & Policy Track
This track combines a solid foundation in Artificial Intelligence with skills-oriented training on how to connect science to real-world issues in society. In addition to in-depth courses and a small academic research project in AI, this track includes a six-month internship focused on applying scientific insights in business, policy, consultancy, or administration.

Please be advised that students of the Faculty of Science and Engineering are expected to adhere to our Bring Your Own Device (BYOD) policy, ensuring seamless integration of personal electronic devices for academic purposes. For more detailed information on our BYOD policy, please visit our webpage.

Programme options:
Machine Learning (specialization)
Hybrid Intelligence (specialization)
Robotics (specialization)
Multi-Agent Systems (specialization)
AI Engineering (specialization)
Science, Business & Policy Track (track)

Study abroad is optional

Exchange is possible, for example as part of your Master thesis. All our science and engineering programmes offer study abroad possibilities at a number of partner institutions. Our partners include top-100 universities in Europe (for example in Germany, UK, and Sweden) and in the USA, China, South-East Asia, and South America. Our exchange programmes have a typical duration of one semester and count toward your final degree.

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Artificial Intelligence

Once you have obtained your Master's degree in Artificial Intelligence, you can apply your research & development skills in workplaces such as air traffic and space labs, to ensure that intelligent and innovative technologies are included in the design process. You could also opt for a research role, either at a university (PhD study) or a research institute like Applied Scientific Research (TNO).

This Master's programme excels thanks to its dedicated staff, who are experienced in investigating and teaching across the full breadth of AI. As a result, students interested in machine learning, logic, and cognition – in any hybrid combination that is so essential for future innovations in AI – will feel at home with us.

Where do graduated master's AI students work at the moment? Bram Wiggers and Daniëlle Metz both graduated recently from this programme.

Bram works for a start-up where he uses AI techniques to reduce the energy usage of data centers. Next to that, he started a company to give workshops on neural networks.

Daniëlle Metz works for a Data Consultancy where she applies the problem-solving and group project skills she learned in the AI Master to do Data Science, Data Engineering, and even Data Governance at several companies in the Financial Sector.

Job examples:

PhD research position
Industrial Research & Development
Software Engineer
Data Analyst

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Artificial Intelligence

This Master's degree programme has a selection procedure; read the information below.

An academic Bachelor's degree in Artificial Intelligence or a related field including the following key subjects: Calculus, Linear Algebra, Probability & Statistics, Advanced Programming, Machine Learning, Advanced Logic, Neural Networks, Research Methodology Skills. The Admission Board determines whether the specific contents of courses meet the admission requirements of the Master programme.

Information about admission possibilities and requirements for students with a Dutch BSc degree (academic or HBO) is published on: https://www.rug.nl/fse/msc-admission

other admission requirements

The Artificial Intelligence Master programme is selective. Selection will be based on academic performance and motivation. After you have registered via www.rug.nl/fse/msc-admission (before May 1st), your application will be reviewed by the Board of Admissions of the programme.

BEFORE YOU APPLY Make sure to visit 'MSc Application Procedure' at

https://www.rug.nl/fse/msc-admission for all the necessary information about the procedure and admission requirements.

Registration procedure

The Board of Admissions will decide whether you can be admitted to the Master's degree programme.

Please fill out this checklist and provide the requested documents:

Provide at least one reference letter and/or contact (name and research institute) we may approach for a reference.

By answering the questions in the Motivation table, explain why you choose to apply for this Master's degree programme.

Describe your pre-education.

Provide a bachelor thesis or another individually written report in English of an academic assignment. If you have not completed such a report, an assignment will be given to you by the Board of Admissions.

Curriculum Vitae.

Do you prefer an early decision on your request of admission? Do not wait until 1 May, but use one of the earlier deadlines for this Master's programme (for a course start on 1 September). If the University of Groningen has received your complete application before, then you will receive a decision no later than:

Application – Decision:

1 December – 15 January

1 February – 1 March

15 March – 15 April

1 May – 15 June

Selection procedure

This means that an applicant must both meet the admission requirements and successfully complete a selection procedure in order to be admitted to the Master's degree programme.

Application deadlines

Type of student Deadline Start course

Dutch students 01 May 2025 01 September 2025

EU/EEA students 01 May 2025 01 September 2025

non-EU/EEA students 01 May 2025 01 September 2025

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Artificial Intelligence - Impressionen zum Masterstudium

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Übersicht der Masterstudiengänge - University of Groningen

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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!

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