Natural Language Processing


Natural language processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics. NLP systems can process and understand human language.  The past decade has witnessed several breakthroughs in NLP which have resulted in an immense growth in the importance of NLP. Enabled by cloud computing, big data technologies and machine learning, NLP has clearly entered the mainstream as these technologies can now be applied to handle large volumes of text data at an unprecedented speed. NLP solutions deliver immense value for organizations across a wide range of different sectors, from digital communications to healthcare and medicine to finance, marketing, and retail. Some of the most common and proven applications of NLP in the industry today are:

  • Spell checks (e.g. Grammarly)
  • Chatbots
  • Text classification 
  • Automatic summary generation
  • Language translation
  • Sentiment analysis
  • Market intelligence
  • Virtual assistance (e.g. Alexa and Siri)
  • Automated language translation (e.g. Google Translate, Microsoft/Skype Translator)

The consequence of the enormous growth in NLP-based applications is that NLP is one of the 7 most in-demand tech skills to master in 2021. By 2025, the global NLP market is expected to reach over $34 billion. The logical implication is that universities urgently need to include NLP in the informatics and data science curriculums to optimally prepare their students for the job market and allow them to profit from the ample opportunities that arise across many industries.  This holds especially true for Swiss Universities of Applied Sciences.

Verantwortliche Person:
Dr. Woo Shao Jü
Standort (angeboten):
Buchs, Waldau St.Gallen
Mathematik, Informatik
Empfohlene Module:
Vorausgesetzte Module:
Zusätzlich vorausgesetzte Kenntnisse:

Ebenfalls vorausgesetzt sind die beiden Module Elektrotechnik & Lineare Algebra I und Elektrotechnik & Lineare Algebra II.

Standard-Modul für Systemtechnik BB STD_05(Empfohlenes Semester: 8)
Standard-Modul für Systemtechnik VZ STD_05(Empfohlenes Semester: 6)

Das Modul findet im Frühlingssemester statt und wird Online angeboten.

Kurse in diesem Modul