This Master’s specialisation has a course load of 120 ECs (two years) and the programme combines foundational knowledge, specialised expertise, and real-world experience, culminating in an extended research project or internship.
Compulsory Courses
Artificial Intelligence is rapidly transforming society, raising important societal, ethical, and legal challenges. As an AI professional, you’ll need more than just technical skills—you’ll need a critical mindset and strong academic professionalism. All AI students follow a set of compulsory courses (18 EC) that provide this foundation, namely, advanced Academic & Professional Skills, Ethics for AI, AI Research Colloquium and a Personal and Professional Development Elective. These courses prepare you to responsibly contribute to the development and application of intelligent systems in a global context.
Specialisation Courses
You will follow 12 EC of core courses for the Machine Learning and Neural Computing specialisation, with a focus on either Machine Learning or Neural Computing. These mandatory courses build the theoretical and practical foundation needed for advanced work in both tracks.
Track courses
You can further tailor your study with a focus on either Machine Learning or Neural Computing by choosing a track, that allow you to deepen your expertise within Machine Learning or Neural Computing.
Machine Learning
In the Machine Learning track (27 EC), you will develop deep technical expertise in core AI technologies, including deep learning, diffusion models, large language models, and scientific machine learning. You will also explore how these methods are applied in real-world domains such as the natural sciences, healthcare, and industry. Your Master’s thesis will give you the opportunity to contribute to the state of the art—either through theoretical or applied research—by working on academic projects with the department or in collaboration with our industrial partners.
Neural Computing
In the Neural Computing track (27 EC), you will focus on the development of brain-inspired technologies that offer efficient, flexible alternatives to conventional AI. Key topics include Neuromorphic Systems and Brain-Computer Interfaces. You’ll gain interdisciplinary knowledge spanning computational neuroscience, control theory, electrical engineering, and edge computing. In your thesis, you’ll apply this knowledge by developing your own neural-inspired systems — advancing both our understanding of the brain and the future of intelligent technology.
Free Electives
In addition, you’ll have 18 EC of free electives, giving you the freedom to take any Master’s-level course at Radboud University or at a partner institution abroad. This flexibility allows you to shape your programme around your academic interests and career goals.
Extended Research Project & Internship
To complete the programme, you will carry out a 45 EC Extended Research Project, where you apply your knowledge to an in-depth AI challenge. You can conduct your project within the AI department, at one of our research institutes (e.g., the Donders Institute or Behavioural Science Institute), or in collaboration with an external partner such as Philips, TNO, or a tech start-up. Alternatively, you may also choose to carry out a 15 EC internship project and a 30 EC thesis project, allowing you to gain practical experience in a company or research lab. This is a valuable opportunity to develop additional skills, expand your network, and test your interests in a real-world setting.