Data Science & Intelligent Analytics PT
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Software Development for Data Science 1 Lab

level of course unit

Master course

Learning outcomes of course unit

Graduates consolidate their knowledge in the application of software development concepts in the area of data science. They have broad applicable knowledge in the area of integration with other software systems, the usage of design patterns and the structure of efficient and scalable data-driven application architectures.

prerequisites and co-requisites

not specified

course contents

The content of the integrative course “Software Development for Data Science 1” is consolidated in the lab by means of practical exercises. Acquired knowledge is dis-cussed within the group, thus providing profound insights and a consolidation of the material that was theoretically discussed in the integrative course.

recommended or required reading

- Häberlein, T. (2016) Informatik: Eine praktische Einführung mit Bash und Python. 2. Auflage, De Gruyter Oldenbourg, Berlin (ISBN: 978-3110496864).
- Sommerville, I. (2015) Software Engineering, Global Edition. 10. Auflage, Pearson Education, London (ISBN: 978-1292096131).
- Williams, L.; Zimmermann, T. (2016) Perspectives on Data Science for Software Engineering. 1. Auflage, Morgan Kaufmann, Burlington (ISBN: 978-0128042069).
- Crawley, M. J. (2007) The R Book. 1. Auflage, John Wiley & Sons Ltd, Chichester (ISBN: 978-0-470-51024-7).
- Bowles, M. (2015) Machine Learning in Python: Essential Techniques for Predictive Analysis. 1. Auflage, John Wiley & Sons Ltd, Chichester (ISBN: 978-1118961742).
- Lutz, M (2013) Learning Python. 1. Auflage, O'Reilly Media, Farnham.

assessment methods and criteria

Group work
Performing exercise tasks

language of instruction


number of ECTS credits allocated


course-hours-per-week (chw)


planned learning activities and teaching methods

Group work
Performing exercise tasks
Interactive workshop

semester/trimester when the course unit is delivered


name of lecturer(s)

Huber Stefan , MA

year of study


recommended optional program components


course unit code


type of course unit


mode of delivery

in-class course

work placement(s)



Mitarbeiterfoto Karsten Böhm
Prof. (FH) Dipl.-Informatiker Karsten Böhm
Director of Studies
+43 5372 71819 133
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