New developments, for example in science, economy, law and technology, lead to large and complicated data sets. To interpret these data appropriately (e.g. in the context of patient or customers' data, stocks and shares, as well as weather and climate change), a knowledge of statistics, computer science and mathematics is required.
The necessary knowledge for in-depth data analyses is taught. For this purpose, key skills from the fields of statistics, mathematics and computer science as well as fields of application are unified. Hence, the students represent an interface of those fields, they are able to work in interdisciplinary teams and to communicate results appropriately.
This interdisciplinary Data Science program is a joined project of the Faculties of Statistics, Computer Science and Mathematics under the general management of the Department of Statistics.
The basics of the study program are covered in the first year. This includes a sound introduction to mathematical theory (applied analysis and linear algebra), computer science (data structures, algorithms, programming) as well as probability and statistics. In the second and third year, the study program offers choices in the fields of advanced mathematical, programming and statistical modeling methods. The management and processing as well as the representation and interpretation of data is taught. Knowledge and application of software is deepened, especially with regard to efficient algorithms.
From the beginning, a strong emphasis is put on case studies and generally on applications, in both the elective and required modules of the study program. These are further enhanced in the thesis.
All mandatory courses are taught in German, elective courses in English may be offered.
The study program consists of 19 modules, including 3 months for the thesis. More information about the course content and course modules can be found below.
The broad content of the Bachelor program will allow the students to choose the appropriate solutions to a wide range of problems e.g. in economy, industry, biology or any area of applied science. It will also allow them to continue their studies, e.g. in our Data Science Master program or other related Master programs. Our Data Science graduates have an exquisite knowledge of methods for big data and therefore are highly sought after in various fields of work.
Note: In each case, the terms of study are relevant; the recommended course of study represents only a possibility.