Is operations research connected to data science
The master’s course Mathematics for Finance, Insurance and Management (Business Mathematics) exists since the winter semester 2007/08. You can start your studies in the winter and summer semesters. The course can be carried out full-time (4 semesters) and part-time (8 semesters).
In our four-semester master’s degree in Business Mathematics (M.Sc.), the mathematical basics, new methods and current procedures in the three specializations are taught Financial mathematics, Actuarial and Statistics / Operations Research / Data Science conveyed. These include:
- the design, evaluation and risk measurement of financial, investment and insurance products (after the financial crisis),
- risk and quality management (especially in the context of quantitative requirements according to e.g. IFRS, Basel III / IV, Solvency II, UCITS / AIFM),
- the planning, control, simulation and optimization of business processes taking into account the information obtained from large amounts of data (big data) using mathematical-statistical methods (data science and machine learning) and
- scientific work in research and development departments (in individual cases also preparation for doctoral studies).
The course content combines application relevance and scientific depth. In the projects and case studies, the students examine practical tasks that combine mathematical models, modern management methods and data science applications. With the master's thesis as a thesis, proof is provided that you are able to work on a topic with a scientific focus.
The courses are divided into different module groups, on the one hand
- the Mathematical basics (e.g. on measurement and integration theory, time series analysis & stochastic processes, risk theory & management, multivariate data analysis) as well as social and cultural sciences and projects
but also the general deepening in the three subject areas of the course
- Financial mathematics (Derivatives I, Derivatives II, Derivatives III [Credit Derivatives and Credit Portfolio Models], Computational Finance Project, Advanced Computational Finance, Advanced Topics in Financial Mathematics),
- Actuarial (Non-life insurance mathematics, health & pension insurance mathematics, advanced methods of non-life insurance, special actuarial topics),
- Statistics / Operations Research / Data Science (Nonlinear & Stochastic Optimization, Statistical Methods of Quality Management, Selected Chapters of Game Theory, Data Mining & Machine Learning, Computer-Aided Methods in Statistics / OR / Data Science, Advanced Topics in Statistics / OR / Data Science),
- mathematical electives for further deepening (e.g. approximation theory, theory and numerics of partial differential equations, functional analysis, function theory, discrete mathematics, algebraic and topological structures) and
- Elective courses in business informatics (Machine learning, applied quantitative methods [project simulation], coding theory and cryptography, big data, multi-agent systems, database systems, data-driven corporate management, advanced analytics).
If you have any further questions, the department's secretariat and the academic advisors will be happy to help.
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