The WASP AI Graduate School provides added value on top of the existing PhD programs at the partner universities, providing unique opportunities for students who are dedicated to achieving international research excellence with industrial relevance.
The graduate school will organize a number of activities to help students form a strong and lasting multi-disciplinary international, academic-industrial professional network. A yearly international study trip and a yearly winter conference, to provide a friendly community for constructive feedback to the PhD Students.
The graduate school aims to establish a strong multi-disciplinary and international professional network between PhD-students, researchers and industries, and to help creating new research collaborations, both within academia and with industry.
There are five mandatory core courses for all students within the WASP AI graduate school:
- Deep Learning and GANs, 6 credits
- Graphical Models, Bayesian Learning, and Statistical Relational Learning, 6 credits
- Learning Theory and Reinforcement Learning, 6 credits
- Large Scale Machine Learning, 6 credits
- Ethical, Legal, Societal and Economical Aspects of AI, 3 credits
Additionally, the following elective courses are offered:
- Topological Data Analysis, 6 credits
- Learning Feature Representations, 6 credits
- Deep Learning for Natural Language Processing, 6 credits
- WASP Project Course, 6 credits
For questions, please turn to the AI Graduate School Management Group.