Data Science & Intelligent Analytics PT
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Academic Methods

level of course unit

Master's course

Learning outcomes of course unit

The following skills are developed in the course:

- Students know the rules through which academic methods function.
- Students can apply these rules on the basis of a specific project.
- Students can write an exposé, coordinating problem definition, research question and methodological approach.

prerequisites and co-requisites

3rd semester: No prerequisites

course contents

Students are introduced to the theory of science and academic methods. The goals of academic methods are dis-cussed and applied to the students' own problems. During the course, the students will therefore develop a first draft exposé for a Master thesis.

recommended or required reading

PRIMARY LITERATURE:
- Poser, H. (2001): Wissenschaftstheorie. Eine philosophische Einführung (Ed. 1), Reclam, Dithingen (ISBN: 978-3150181256)

SECONDARY LITERATURE:
- Franck, N. (2017): Handbuch Wissenschaftliches Arbeiten (Ed. 3), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3825247485)

assessment methods and criteria

Exposé on the Master thesis

language of instruction

German

number of ECTS credits allocated

2

eLearning quota in percent

50

course-hours-per-week (chw)

1

planned learning activities and teaching methods

The following methods are used:

- Lecture with discussion
- Interactive workshop

semester/trimester when the course unit is delivered

3

name of lecturer(s)

Prof. (FH) Dipl.-Informatiker Karsten Böhm

course unit code

MWA.1

type of course unit

seminar-degree

mode of delivery

Compulsory

work placement(s)

none