Huge amounts of data are generated every day in almost all areas of life – whether on mobile phones, in medicine, energy supply or logistics. Many of these data treasures harbour great potential for society, business and science. Even if machine learning facilitates data analysis in many cases, highly qualified people are still indispensable for analysing data, interpreting it correctly and further developing the models. For this reason, Graz University of Technology (TU Graz) and the University of Graz have developed the new Master’s degree programme in Data Science as part of their NAWI Graz cooperation: The course combines mathematics, statistics and computer science to provide profound education in which students acquire skills in areas such as data analysis, forecasting, optimisation, information integration and machine learning. The two-year degree programme taught in English starts in October 2024.
Teaching what AI methods are based on
“We are currently experiencing a boom in the use of artificial intelligence in data analysis. But only a few people actually understand how the models work, what they can and cannot do,” says Siegfried Hörmann, co-chair of the curricular committee at the Institute of Statistics at TU Graz. “We want to teach our students what these methods are based on and how they can develop or adapt them themselves. Our strong focus on these fundamentals sets our programme apart from similarly labelled, primarily application-oriented degree programmes at other universities.” The degree programme also teaches the ethical and legal principles that data scientists must take into account in their work.
Applications range from medical imaging to autonomous driving
In addition to theory, students on the Master’s degree programme in Data Science deal with application-oriented questions, such as how data can be turned into images. Mathematics, which forms the foundation for machine learning and artificial intelligence (AI), provides essential answers to this question. “With the help of AI, even small amounts of data can provide highly precise images,” says Martin Holler, chair of the curricular committee at the Institute of Mathematics and Scientific Computing at the University of Graz. For example, AI makes computerised and magnetic resonance imaging significantly more accurate, which in turn can enable better diagnoses. The utilisation of huge amounts of data is also essential for autonomous driving. After all, the computer has to recognise the environment precisely and react appropriately to the respective situation in real time.
Excellent career prospects
Graduates of the course can pursue a variety of careers in research, development and industry, for example as data analysts who process, evaluate and visualise large amounts of unstructured data. As data scientists, they develop machine learning and artificial intelligence models in order to use them as a basis for predictions and decisions. Alternatively, graduates can dedicate themselves to data management as data engineers in a research institution or company.
Bachelor’s degree in natural sciences or technology as a prerequisite
The new Master’s degree programme is open to many interested parties; the prerequisite is a Bachelor’s degree with a scientific or technical focus, for example in mathematics, physics or computer science. Bridge courses in the first semester help students from different subject areas to bring their knowledge up to a common level.
