Natural Language Processing

Natural Language Processing (NLP) concerns the interaction between computers and human language, in particular how to build systems to process and analyze large amounts of human language data. It has become an important technology in many parts of computer science, facilitating key applications of large-scale text understanding, automatic question answering, knowledge base construction, information retrieval, text or speech-driven dialogue agents, translation, text summarization, etc.

This course aims to introduce the principles and techniques for Natural Language Processing. Through the lectures, assignments, and the group project, students will gain an understanding of classic and modern techniques for language understanding and generation and learn the skills to design, develop, and evaluate their own Natural Language Processing systems and applications.

The final grade of the course consists of the following components:

• Individual Report: individual literature survey and assignments (weighting 20%)

• Group Report: group project, written report and interview (weighting 80%)

Final grade calculation = 0.2 * Individual Report + 0.8 * Group Report

A passing final grade for the course can only be earned when for all components at least a 5.0 is earned, and the weighted final grade is at least a 5.8.

In case of an insufficient final result, repair options may exist in accordance with Article 17A, Times and number of examinations, sub 1, of the Teaching and Examination Regulations, for:

• Individual Report: Repair opportunity

• Group Report: Repair opportunity

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).