Data Science & Intelligent Analytics PT
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Master Thesis Seminar

level of course unit

Master's course

Learning outcomes of course unit

The following skills are developed in the course:

- Students are aware of how scientific reviews are conducted.
- Students are also aware of how to present results to a scientific community.
- Students can critically question scientific findings.

prerequisites and co-requisites

No prerequisites

course contents

The course accompanies the students while they draft and write their master thesis. The colloquium will therefore present and discuss the question/hypothesis and structure of the Master thesis. In addition, the scientific methodology of the Master thesis is discussed and questioned and advice is given on the formal design of the Master thesis.

recommended or required reading

PRIMARY LITERATURE:
- Franck, N. (2007): Handbuch Wissenschaftliches Arbeiten (Ed. 2), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3596151868)

assessment methods and criteria

Final presentation

language of instruction

German

number of ECTS credits allocated

2

eLearning quota in percent

0

course-hours-per-week (chw)

1

planned learning activities and teaching methods

The following methods are used:

- Interactive workshop
- Lecture with discussion

semester/trimester when the course unit is delivered

4

name of lecturer(s)

Prof. (FH) Dipl.-Informatiker Karsten Böhm

course unit code

MWA.2

type of course unit

seminar-degree

mode of delivery

Compulsory

work placement(s)

none