Master of Science in Data Science

This Master's degree programme imparts skills that are necessary in order to handle the advancing digitisation of many areas of the physical and life sciences. This concerns topics such as the collection, processing, analysis and interpretation of large digital data sets. To this end, the Master's degree programme conveys the key aspects of modern data science, which is characterised by a blending of the central fields of mathematics, statistics, computer science and machine learning, taking application-related issues into account. With in-depth education in the corresponding branches of mathematics, statistics and computer science as well as in the relevant application fields of the physical and life sciences that engage in quantitative work, this programme imparts the skills needed to recognise the relevant problems in data analysis, develop and apply appropriate mathematical or computer science solutions and correctly interpret the results within the specific application context. The following profile areas are offered to students: Data Science in the Life Sciences: The Life Science track is designed for students aiming to apply data science methodologies to biological, biomedical, and health-related fields. This specialisation integrates core data science principles with domain-specific knowledge pertinent to the life sciences. Data Science Technologies: The Data Science Technologies track is tailored for students aiming to deepen their expertise in computational and algorithmic aspects of data science. This specialisation emphasises advanced technical skills, preparing graduates for roles in software engineering, artificial intelligence, and big data infrastructure. Overview The Master’s degree programme comprises 120 credits. These credits are split between modules totalling 90 credits and the Master’s thesis with its accompanying colloquium, which comprises 30 credits. The Master's degree programme is divided into a fundamental area comprising 30 credits (to be completed in the first semester) and a profile area comprising 60 credits (second and third semester). The Master’s thesis is usually written in the fourth semester. Fundamentals The following modules must be completed as part of the fundamental area comprising 30 credits: Module: Introduction to Profile Areas  Module: Statistics for Data Science Module: Machine Learning for Data Science  Module: Programming for Data Science  It is recommended students complete the modules of the fundamental area in their first semester. Profile In the second and third semester, students may specialise in one of the following two profiles: Data Science in the Life Sciences Data Science Technologies Students of both profiles must complete a mandatory module "Ethical Foundations of Data Science" and a 15 credit elective area, in which complementary courses from the other profile or other programmes can be selected.  Master's thesis with accompanying colloquium The Master's thesis is usually written in the fourth semester after at least 60 credits have been completed. The processing time is 23 weeks. During this time, the students should give a presentation on the progress of their work. For more details, please see the programme website and study regulations.