Advanced Topics in Natural Language Processing

Course description

Content 
The course presents selected advanced topics within NLP. The topics vary from time to time due to the subjects’ development, but may be within: Natural language understanding, language representation, multitask learning, learning from multiple modalities, deep generative models, reinforcement learning, generative adversarial learning.

Prerequisites
Good programming experience and a solid mathematical background and assumptions similar to Natural Language Processing.

Practical information

The course is offered as a single-subject course at the Faculty of Science. Single-subject courses typically run for seven to nine weeks with scheduled activities approx. one day per week.

You will be attending the course together with full-time students from the Faculty of Science, and you must meet various admission requirements. The course ends with an exam.

The number of places is limited, and they are allocated on a first-come, first-served basis, so do not delay your application!