Topic outline

  • General

    The goal of this course is to become familiar with methods for the processing of natural language.

    After attending the course, the student knows how statistical and adaptive methods are used in information retrieval, machine translation, text mining, speech processing and related areas to process natural language contents. Furthermore, the student can apply the basic methods and techniques used for statistical natural language modeling including, for instance, clustering, classification, Hidden Markov models and Bayesian models.

    Many core applications in modern information society such as search engines, social media, machine translation, speech processing and text mining for business intelligence apply statistical and adaptive methods. This course provides information on these methods and teaches basic skills on how they are applied on natural language data. Each topic is handled by a high level expert in the area.

    The requirements for passing the course in 2019 include an exam and a small project group work.