Data Science is a hot topic, which gains in importance as a cross-sectional topic almost everywhere including natural sciences, engineering, and medical science.
Data Science deals with the extraction of knowledge and usable information from data. The available data sets are often very large, heterogeneous, and partially unreliable. Data Science is an interdisciplinary field with its roots in computer science, mathematics, and statistics and it has a strong link to various application areas.The essential constituents of data science are data analysis and systems engineering.Therefore, this course of study is going to convey modern methods of data analysis as well as algorithms and techniques for the development of information systems.
The students are provided the possibility of specialization within the framework of an application area:
The curriculum is divided into a foundational area with about 60 CP and an area of specialization with about 30 CP, plus some room for "additional competences" with maximum 12 CP. Courses offered in the specialisation area form the basis of the final thesis with 30 CP. Following the idea of the Integrated Interdisciplinary University, the final thesis can be written not only in the core fields computer science and mathematics, but also in one of the following application fields: Business Analytics, abbreviated BA, Computational Life Science abbreviated CLS, Computational Social Science abbreviated CSS, and Physics abbreviated P.
The foundational area covers the main methodological foundations of data science. It consists of a list of selected modules from computer science and mathematics, among them the introductory modules "Introduction to Data Science" and "Mathematics of Data Science". An additional part of the core area is the module "Ethics of Data Science".
As "additional competences", students have the possibilities to choose up to 12 CP in courses from a wide range of areas. This includes nontechnical competences, such as German language classes for foreign students, as well as certain modules from the Bachelor Degree Programs in computer science and mathematics. The second part of the curriculum is the specialisation area, leading towards the final master's thesis. While the specialisation areas "Computer Science", "Mathematics", and "Computer Science and Mathematics" focus on strong methodological competences, a specialisation in one of the application areas, as listed above, enables students to work on applied data science problems in the context of another discipline.
Data-Science methods are used in a broad spectrum of applications in science and industry.
Data science gains increasing importance in the industry due to the desire and the need for utilizing the information that becomes available because of the comprehensive networking of terminal equipment - Internet of Things, Industry 4.0 - the widespread use of social networks and the availability of immense amounts of measurement, multimedia and simulation data. In addition to the companies from ICT, financial and service sectors, also "classical" industrial companies look for graduates with this qualification profile.
Data Science is also a hot research topic, which gains in importance as a cross-sectional topic almost everywhere including natural sciences, engineering, and medical science.
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