Course Content

This study programme enhances your analytical skills and deepens your knowledge in Machine Learning, Big Data, and Business Intelligence. You will learn practical techniques like Deep Learning and Data Visualization. These skills enable you to tackle societal challenges, such as in healthcare or environmental protection. Data Science and Artificial Intelligence pave the way for a forward-looking career full of innovations.

Key areas 

The program consists of three main areas:

• Data Science: At the core of Data Science are key topics such as statistics, programming, and data visualization. This is complemented by the teaching of legal and ethical principles in the field of artificial intelligence.
• Artificial Intelligence explores exciting fields such as Machine Learning, Deep Learning, Generative AI, Computer Vision, and Natural Language Processing. You will learn how to apply these technologies in practice, from analyzing large datasets to developing innovative AI solutions.
• Business immerses you in the world of Digital Business and Business Intelligence. Gain solid knowledge of economic fundamentals and learn how digital technologies transform business models and how data-driven decisions propel companies forward.

Use the elective courses in the 5th and 6th semesters to further tailor your studies.
 

Vocational Internship (4th semester)

The internship must be completed in the 4th semester (worth 20 ECTS). Students independently contact their preferred companies, with access to the program's extensive partner network.

During the internship, you’ll have the opportunity to apply your knowledge, gain first insights into the business world, and gather valuable experience.

Semester Abroad or European Project Semester (5th semester)

An essential part of the program is the 5th semester, where students form groups to solve a data-driven problem within a project.

The 5th semester can also be completed abroad at a partner university.

Practical Training

The study programme Data Science and Artificial Intelligence¹ maintains intensive cooperation with important partners from the economy and science. This ensures that the study content covers the requirements of the practical experience and takes into account future developments.

The inclusion of external lecturers also enables you to build up practice-relevant knowledge. Additionally, practical transfer and application competencies are promoted by two vocational internships and an international-project semester in which a task formulation from the economy is treated in international teams.

Why Data Science?

A Human View

Despite the many fully automatic enquiry possibilities through artificial intelligence or deep learning, the most important task is often left to humans. Although an AI can detect patterns, they are not necessarily able to detect cause and effect. If one wants to know why the detected patterns occur, it is the task of the data scientist to comprehensibly explain causal relationships.

¹ subject to accreditation by AQ Austria