"I keep saying that the sexy job in the next 10 years will be statisticians, and I'm not kidding.”
Hal Varian, chief economist at Google, 2009.
As a scientific discipline, statistics is concerned with methods to draw inference based on experimental or empirical data, and to quantify the uncertainty of estimates and predictions precisely. The methods and models of probability theory and statistics are rigorously formulated as mathematical theories in order to be able to study their properties and demonstrate their validity independently of specific application examples.
Data collection and modeling is also an important aspect. The increasing digitization and the ever increasing amount of data has posed new challenges in this area. Methods to address these tasks are often collected under the name data science.
In the Master's program in Statistics and Data Science, on the one hand, the most important models and concepts of statistics, probability theory, financial mathematics and actuarial science are introduced. On the other hand, students are also familiarized with the most important methods of Computer Science to handle and analyze large amounts of data. The students get acquainted with recent research in these fields and are guided to work on a scientific project (Master's thesis).
A Bachelor of Science in Mathematics is a prerequisite for the Master's program in Statistics and Data Science. However, students with a Bachelor's degree or an equivalent qualification in a different field may also be admitted to the program in some circumstances. The main requirement is that this degree should contain at least 60 ECTS credit points in Mathematics and sufficient background in Statistics.
Having obtained a Master's degree in Statistics and Data Science with excellent grades, it is possible to enter our research-oriented PhD program.