Data Science & Intelligent Analytics PT
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Master Thesis

level of course unit

Master course

Learning outcomes of course unit

Students learn how to properly perform their independently developed scientific research within the context of the master thesis and portray it in written form in a comprehensive scientific paper.

prerequisites and co-requisites

not specified

course contents

The master thesis topic is selected from the topical range of the study program. The developed problem area is prepared based on an academic paper – this, of course, is done independently and without the help of others (stating sources and means). This modus operandi ensures that students are able to work on a problem in a scientific and application-oriented manner. Students are to independently search for topics and develop an out-line and time schedule – first and foremost by critically examining possible problems and hypotheses. The supervisor guides the student as scientific methodology, formal design and time management are discussed within the context of individual coaching.

recommended or required reading

- Atteslander, P. (2010) Methoden der empirischen Sozialforschung. 13. Auflage, Erich Schmidt Verlag, Berlin (ISBN: 978-3-503-12618-7).
- Eco, U. (2010) Wie man eine wissenschaftliche Abschlussarbeit schreibt. 13. Auflage, UTB, Stuttgart (ISBN: 978-3825215125).

assessment methods and criteria

Master Thesis

language of instruction

German or English

number of ECTS credits allocated


course-hours-per-week (chw)


planned learning activities and teaching methods


semester/trimester when the course unit is delivered


name of lecturer(s)

Head of studies

year of study


recommended optional program components


course unit code


type of course unit

Master Thesis

mode of delivery

Writing a master thesis

work placement(s)



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