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, Spring 2019, 6 credits
- Graphical Models, Bayesian Learning, and Statistical Relational Learning, Autumn 2019, 6 credits
- Ethical, Legal, Societal and Economical Aspects of AI, Spring 2020, 3 credits
- Learning Theory and Reinforcement Learning, Spring 2020, 6 credits
- Large Scale Machine Learning, Autumn 2020, 6 credits
Additionally, the following elective courses are offered:
- Topological Data Analysis, Autumn 2019, 6 credits
- Deep Learning for Natural Language Processing, Spring 2020, 6 credits
- Learning Feature Representations, Autumn 2020, 6 credits
- WASP AI Project Course, Spring 2021, 6 credits
For questions, please turn to the AI Graduate School Management Group.