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International Master´s program
Data Science

Master's program Advanced and Computational Mathematics

Specialization in Data Science

1. sem. Levelling up course 5 ECTS
One Basic Course from:
Algebraic Geometry, Algebraic Topology,
Differential Geometry, Fourier Analysis, Functional Analysis II,
Geometric Analysis, Stochastic Analysis, Stochastic Processes
One Basic Course from:
Inverse Problems, Numerical Methods for
ODEs, Numerical Methods for PDEs, Numerical Linear Algebra,
Numerical Optimization
One Basic Course from:
Introduction to Data Science, Mathematical
Foundation of Learning Theory, Mathematical Methods for
Uncertainty Quantification, Matrix Methods in Data Science
2. to 3. sem. 4-5 courses to be chosen out of: 38 ECTS
Discrete Optimization; Dirichlet Forms, Markov Processes, and Semigroups; Fourier Analysis; Game Theory; Graph Theory; Hilbert Space Methods; Introduction to Data Science; Introduction to Insurance Mathematics and Mathematical Finance; Introduction to Wavelet Theory; Inverse Problems; Mathematical Foundations of Big Data Analytics; Mathematical Foundations of Learning Theory; Mathematical Methods for Uncertainty Quantification; Matrix Methods in Data Science; Numerical Methods for ODEs; Numerical Methods for PDEs; Numerical Linear Algebra; Numerical Optimization; Optimization in Machine Learning; Statistics in Data Science; Stochastic Analysis; Stochastic Processes; Times Series Analysis; Variational Methods
3. sem. Research Seminar or Modelling Seminar 8 ECTS
4. sem. Master's Thesis 30 ECTS
1. to 3. sem. Language Courses
German (at least level A2), Optional language courses
A more detailed description of the content of each course offered within this program can be found on the Course content website. Please be aware that despite the possibility of specializing in Data Science, the International Master and Ph.D. program is a program in Mathematics and is distinct from the Master program Data Science offered by the Faculty of Mathematics. The latter program is not an international program and requires proficiency in German of level C1 at least.
Students with excellent results in their Master's degree qualify for the Ph.D. program. The Ph.D. program places particular importance on developing the ability to conduct self-reliant scientific work. Next to the immersion in the field of specialization, Ph.D. students are encouraged to attend respective lectures and seminars on latest research and actively participate in research group work.