Aus dem Modulhandbuch Master PO 2019:
Inhalte: The goal of this course is to give participants a first gentle introduction and solid conceptual
grounding in what has been called ‘data science’, i.e. experimental work that is data-driven and empirical.
The focus is on methodology, defining an experimental protocol, devising hypotheses, thinking about
measuring success, but also on more practical approaches like basic machine learning methods (both
supervised and unsupervised) and natural language processing approaches (like part-of-speech tagging,
named entity recognition/classification/resolution, and parsing) and the introduction to popular tools. The
course also demonstrates some practical applications of the techniques shown, and deepens the students’
skills via practical exercises.
(Ziel dieses Moduls ist es, den Teilnehmern eine erste Einführung und fundierte konzeptionelle Grundlagen
im Bereich ‘Data Science’ zu vermitteln. Dies beinhaltet experimentelle, datengetriebene und empirische
Arbeit.)
- Trainer/in: Chrisowalandis Deligio
- Trainer/in: Karsten Tolle