Master's program Advanced and Computational MathematicsSpecialization in Advanced Pure Mathematics |
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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 |
24 ECTS | |
2. to 3. sem. | 4-5 courses to be chosen out of: | 38 ECTS | ||
Algebraic Geometry; Algebraic Topology; Complex Geometry; Differential Geometry; Dirichlet Forms, Markov Processes, and Semigroups; Fourier Analysis; Fractals; Functional Analysis II; Geometric Analysis; Graph Theory; Harmonic Analysis; Hilbert Space Methods; Mathematical Foundation of Learning Theory; Stochastic Analysis; Stochastic Processes; Times Series Analysis | ||||
3. sem. | Research Seminar | 8 ECTS | ||
4. sem. | Master's Thesis | 30 ECTS | ||
1. to 3. sem. | Language Courses German (at least level A2), Optional language courses |
15 ECTS |
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.