Applied Mathematics
Mittweida University of Applied Sciences
at University of Bremen · Bremen
Duration
4 semesters
Tuition
No tuition fees
Intake
Winter semester, Summer semester
Mode
Full Time
The Master’s program in Industrial Mathematics and Data Analysis at the University of Bremen focuses on equipping students with the analytical skills and quantitative methodologies essential for solving complex problems in various industrial settings. The curriculum is designed to blend theoretical mathematics with practical applications in data analysis, allowing students to tackle real-world challenges through rigorous mathematical models and data-driven decision-making.
The program spans four semesters, comprised of core modules in advanced mathematics, statistical analysis, and computational methods, alongside electives that allow students to tailor their learning experience. This structure is in line with the European Credit Transfer and Accumulation System (ECTS), enabling students to earn credits toward their degree. In addition, students typically engage in a thesis during their final semester, which involves research work that contributes to the field of industrial mathematics.
The University of Bremen emphasizes a hands-on approach, particularly through partnerships with local Mittelstand companies and industries, facilitating internships and practical projects. This engagement not only enhances the academic experience but also provides students with valuable networking opportunities in the German job market. This program is best suited for individuals with a strong foundation in mathematics who wish to apply their knowledge in practical, industry-oriented contexts.
It typically takes 4 semesters, with intakes in Winter semester, Summer semester.
Tuition is around No tuition fees. Fees change yearly — confirm with an advisor.
Data Analyst in various industriesOperations Research Analyst in manufacturing and logisticsQuantitative Analyst in financial servicesStatistician in healthcare and researchMathematical Modeler in technology firms
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