Data Science
- Faculty
Faculty of Business Management and Social Sciences
- Version
Version 14.0 of 02/08/2019
- Code of Module
22M0993
- Modulename (german)
Data Science
- Study Programmes
Wirtschaftsinformatik (Master) (M.Sc.)
- Level of Module
5
- Responsible of the Module
Faatz, Andreas
- Lecturer(s)
- Faatz, Andreas
- Bensberg, Frank
- Markovic-Bredthauer, Danijela
- Tapken, Heiko
- Credits
5
- Concept of Study and Teaching
Workload Dozentengebunden Std. Workload Lehrtyp 24 Vorlesungen 7 Vorlesungen Workload Dozentenungebunden Std. Workload Lehrtyp 70 Hausarbeiten 20 Hausarbeiten 29 Hausarbeiten
- Recommended Reading
Field, Andy, Jeremy Miles, and Zoë Field. Discovering statistics using R. Sage publications, 2012.
Witten, Ian H., et al. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, 2016.
Zumel, Nina, John Mount, and Jim Porzak. Practical data science with R. Manning, 2014.
- Graded Exam
- Two-Hour Written Examination
- Portfolio exam
- Homework / Assignment
- Duration
1 Term
- Module Frequency
Only Winter Term
- Language of Instruction
German