Data Science & Intelligent Analytics PT
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Practical Project

level of course unit

English version available soon

Learning outcomes of course unit

The following skills are developed in the course:

- Students can apply their knowledge from the first two semesters in a data-centric project.
- Students can structure and manage a data-centric project.

prerequisites and co-requisites

3rd semester: No prerequisites

course contents

In this course, students work on a real, data-centred project along the entire data value chain (from data collection, integration and storage to analysis and utilization of the data). This allows them to try out the skills they have built up in the first two semesters in a real setting and gain new insights.

recommended or required reading

PRIMARY LITERATURE:
- Patzak, G.; Rattay, G. (2017): Project management: Projekte, Projektportfolios, Programme und projektorientierte Unternehmen (Ed. 7), Linde Verlag, Vienna (ISBN: 978-3714303216)

SECONDARY LITERATURE:
- Schöneck, N. M.; Voß, W. (2013): Das Forschungsprojekt: Planung, Durchführung und Auswertung einer quantitati-ven Studie (Ed. 2), Springer VS, Wiesbaden (ISBN: 978-3531195018)

assessment methods and criteria

Project documentation

language of instruction

German

number of ECTS credits allocated

4

eLearning quota in percent

0

course-hours-per-week (chw)

2

planned learning activities and teaching methods

Coaching within the framework of project implementation

semester/trimester when the course unit is delivered

3

name of lecturer(s)

Prof. (FH) Dipl.-Informatiker Karsten Böhm

course unit code

MDS.4

type of course unit

project

mode of delivery

Compulsory

work placement(s)

none