Data Science for Business (formerly Business Data Analytics: Applications and Tools)

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Content

In the course "Data Science for Business": 

  • You will learn about essential Data Science methods, including clustering and classification techniques (e.g., random forests, SVMs).
  • You will understand process models such as CRISP-DM.
  • You will explore different types of data, including eye-tracking data, click data, neurophysiological data, sales data, and other business-related data.
  • You will gain skills in data visualization and evaluation using programming languages and software tools.

Workload:

  • Attendance time Lecture (2 SWS × 15 weeks): 30 h
  • Attendance time Tutorial (1 SWS × 15 weeks): 15 h
  • Self-study Lecture: 20 h
  • Self-study Tutorial: 50 h
  • Exam preparation: 20 h
  • Total: 135 h
Language of instructionEnglish