Bridging the gap between your subject and IT

Master’s module Digitisation - Data Science

Learning to understand and use big data

Certificate

from the University of Graz

ECTS credit points

24

Module begins

summer semester

Module duration

2 semesters

Languages of instruction

German & English

Added value

practice, network, skills

Help shape the digital transformation!

Digitisation is relevant for many professional groups. In this module, you will acquire key digital technologies (such as big data analytics, artificial intelligence, Internet of Things, data visualisation) for your subject. You will also learn to create prototype solutions for simple problems from your subject area, without having to become a developer!

General Information

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What can you expect?

You will be introduced to:

the basics and possible applications of data-based technologies
data preparation and processing with R
the most important stages of a data science project.

You will study in depth:

data science methods (machine learning, artificial intelligence, data visualisation)
socio-political dimensions and legal framework conditions of digitisation

Together with your team, you will work on the practical implementation of an interdisciplinary case study.

Module curriculum (in German)

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What can you go on to do?

After completion of the master’s module, you will be able to:

recognise the use of design options of data-based technologies for your own subject,
apply basic concepts and tools for simple problems,
understand and competently discuss the technical, economic, socio-political and ethical dimensions of digital transformation,
describe the fundamental legal framework.

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Who can choose the module?

As a student of any master’s or diploma programme, you can choose the master’s module as part of your free elective courses. In the following master’s programmes, the module is also incorporated in the curriculum:

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Application

There are 2 steps to applying for this master’s module:

Complete a brief application form by the application deadline, Oct. 1, 2024–Jan. 15, 2025.
You will receive a message by the end of January 2025 at the latest telling you whether you have been accepted.

Please inform yourself well in advance about the admission requirements.

What can you expect?
What can you go on to do?
Who can choose the module?
Application

3 reasons for choosing this Master’s module

innovative topics

on digital transformation

lots of practice

in implementing data-based technologies

highly relevant

to your subject and job

„The analysis of data is one of the most significant tools of our time. It turns raw data into usable information that serves as the basis for economically and socially relevant decisions. In the Master’s Plus programme, you will learn how to use this powerful tool to profit both people and companies.“

Patrick Ratheiser, CEO - Leftshift One

[Translate to English:] Fotoquelle: Leftshift One

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Patrick Ratheiser, CEO of Leftshift One

Can the right use of data help to make the world a little bit better?

Patrick Ratheiser, CEO and Co-Founder of Leftshift One, explains the advantages of artificial intelligence and why you don't have to be afraid of robots that want to take over the world. AI technologies are powerful tools and support systems that help make economically and socially relevant decisions. In the Module Digitalisation - Data Science, you will learn important tools for data analysis which you can use professionally and beneficially for man and machine.

Module curriculum

In addition to the implementation perspective of data-based technologies, after completing this Master’s module you will also be able to:

understand and competently discuss the central implications of the digital transformation from a technical, humanities, social and economic sciences as well as the ethical perspective,
understand the design options of data-based technologies and formulate requirements for different application contexts,
apply basic concepts and tools for simple problems,
analyse the socio-political dimension of digitisation and
describe the fundamental legal framework.