Quality and Usability

Natural Language Processing

Intergrierte Veranstaltung
(Mohtaj; 6 LP; each SoSe)


Learning Outcomes

The students gain fundamental knowledge of using machine learning methods to process natural language and understanding of different tasks and techniques in natural language processing. It includes knowledge about the advantages and disadvantages of different NLP technologies and also the knowledge of interpreting results of an NLP system. Moreover, the course teaches the evaluation metrics for different NLP tasks like text classification, named entity recognition and keyphrase extraction.


Current fundamental topics in natural language processing are presented in the course. This includes text pre-processing steps, text vectorization and language models. Moreover, different tasks in NLP like text classification, keyphrase extraction, named entity recognition and machine translation and also the evaluation metrics for theses tasks are discussed in the course. The course includes practical project work to apply the taught models on real problems; therefore, basic knowledge of python and machine learning is recommended.

Description of the teaching and learning methods
Studying the online video on the learning platform.
Discussing the topic and questions in the forum and doing the quizzes and projects.

current semester

Time: Tuesday 12 - 2 pm , starts on 26.04.2022

ISIS-Link: https://isis.tu-berlin.de/course/view.php?id=28041

Please note that attendance in the first session of the course is mandatory for registration.
Please check the ISIS page for the zoom link of the first session.

ISIS enrolment key: NLP2022

Location: online

Exam registration: 21.04.2022 - 08.05.2022