Selected Topics in Natural Language Processing

This doctoral level course examines the major challenges and state-of-the-art methods in Natural Language Processing. The topics include computational morphology, syntax, formal and distributional semantics, and discourse analysis.

Course description

The course is seminar-style. The focus is on machine learning for natural language processing, in particular sequence labeling, probabilistic generative models, discriminative methods,and semi-supervised learning. Also of interest are the applications of NLP in machine translation, text mining, information retrieval and extraction. While the emphasis is on the more recent papers from high-profile conferences, we also study the seminal works in the field.

The Selected Topics in Natural Language Processing course is co-lectured by Assist. Prof. Jan Šnajder and Prof. Sebastian Pado from Stuttgart University.

Additional information

The course is offered in English only.
Browse the official course website at

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