Machine learning for statistical NLP: advanced

Master’s level
7.5 credits (ECTS)


In this course, students will get hands-on experience in machine learning for language technology applications, including multimodal applications. This course will cover neural networks and related contemporary techniques and concepts.  Students will improve their machine learning skills by developing simple NLP applications in widely-used programming frameworks and get practice in making and implementing design choices independently.

Prerequisites and selection


Admission to the course requires a passed result in each of the following courses: LT2001 Introduction to programming, 7.5 credits LT2003 Natural language processing, 15 credits Admission to the course also requires a passed result in any one of the following courses: LT2202 Statistical methods, 7.5 credits LT2212 Statistical methods, 7.5 credits LT2222 Machine learning for statistical NLP: introduction, 7.5 credits Language technology skills equivalent to the above will also be accepted for admission.