Module Number

Module Title

Natural Language Processing: A Practical Introduction
Type of Module

Elective Compulsory
Work load
- Contact time
- Self study
90 h
Class time:
30 h / 2 SWS
Self study:
60 h
Duration 1 Semester
Frequency In the winter semester
Language of instruction German
Type of Exam

Exercise, final project

Lecture type(s) Lecture

The term Natural Language Processing (NLP) covers the machine analysis and generation of natural language data. Prominent NLP applications include
Speech recognition, spelling and grammar correction, machine translation, Chatbots, and speech assistance systems. This event provides an introduction to basic concepts and techniques from the subareas of word, sentence and text , sentence and text analysis, e.g. word normalization, semantic word networks, tagging, chunking, parsing, text classification. The course is designed as a practical introduction and consists of Lectures and programming exercises. No linguistic or linguistic or computational linguistic knowledge is assumed; however, general programming knowledge but general programming knowledge must already be available. This is not a programming course! Therefore, the course is intended for advanced bachelor students of of computer science.


Students have basic knowledge of general concepts, resources and procedures in the field of Natural Language Processing (NLP) and can implement these practically in the form of small programmes.

Allocation of credits / grading
Type of Class
Type of Exam
Exam duration
of Module (%)
Prerequisite for participation INFM1110 Practical Computer Science 1: Declarative Programming,

INFM1120 Practical Computer Science 2: Imperative and Object-Oriented Programming
Lecturer / Other Lichte


Last offered Wintersemester 2022
Planned for Wintersemester 2023
Assigned Study Areas BIOINFM2510, INFM2510, INFM3110, MDZINFM2510, MEINFM3210, MEINFM3220