Data Science & Intelligent Analytics PT
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Trends in Data Science

level of course unit

Master course

Learning outcomes of course unit

Students are familiar with current trends within the context of data acquisition, data storage, data analysis and data usage. They are able to assess these trends with respect to a specific task and estimate their potential.

prerequisites and co-requisites

not specified

course contents

Students learn about current topics in data science. Examples:

-Current research emphases within the topical field of data science
-Current solution approaches that have established themselves in practice (e.g. within the context of known companies)
-Trends that are becoming apparent within the topical field of data science (research/practice)

recommended or required reading

Je nach angebotener Inhalten

assessment methods and criteria

Seminar paper or final examination

language of instruction

German

number of ECTS credits allocated

2

course-hours-per-week (chw)

1

planned learning activities and teaching methods

Lecture with discussion
Interactive workshop
Case studies

semester/trimester when the course unit is delivered

4

name of lecturer(s)

Head of studies

year of study

2

recommended optional program components

N.A.

course unit code

DPR.8

type of course unit

SE

mode of delivery

In-class course

work placement(s)

N.A.

Kontaktpersonen

Mitarbeiterfoto Karsten Böhm
Prof. (FH) Dipl.-Informatiker Karsten Böhm
Director of Studies
+43 5372 71819 133
Karsten.Boehmfh-kufstein.ac.at
questions -  Any
Any questions -
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+43 5372 71819 500
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Förderer

Mit Unterstützung von Bund, Land und Europäischer Union: