TKO_2101 Natural Language Processing 5 ECTS
Organised by
Computer Science
Preceding studies
Recommended:

Learning outcomes

The course focuses on the fundamental methods of natural language processing. The students learn how to apply machine learning methods to deal with the ambiguity present in human language at all levels. Working their way from elementary n-gram models to methods of natural language understanding, the students will learn the relevant methods and how to apply them to real-world data, using existing software packages and libraries. The course also lays the methodological foundations for Information Retrieval (TKO_2098) and Text Mining (TKO_2099).

Contents

Language models, morphological and syntactic analysis, computational semantics, deep learning and vector space representations, large-scale data resources, evaluation.

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Exercise(s)
  • In English
Project / practical work
  • In English
Written exam
  • In English

Lectures, hands-on programming exercises, project, exam

Evaluation

Numeric 0-5.

Study materials

Lecture material, online documentation, selected chapters from Jurafsky & Martin - Speech and Language Processing.

Belongs to following study modules

Department of Future Technologies
Department of Future Technologies
Department of Biochemistry
2016–2017
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Department of Future Technologies
DP in Computer Science
DP in Computer Science
DP Bachelor of Science in Techn.(Communication St)
DP in Information and Communication Technology
MDP in Digital Health and Life Sciences (Tech.)
Finnish Study Modules