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International Master and Ph.D. program
Data Science

Master program (Data Science)

1. to 2. sem. Basic courses
Introduction to Data Science
Machine Learning     Matrix Methods in Data Science
Big Data Analytics     Statistics in Data Science
Numerical Analysis
Numerical Methods of ODEs / PDEs
Numerical Linear Algebra
Optimization Methods
Nonlinear optimization
Algorithms for Convex Optimization
3. to 4. sem. Applications and Specialization
Optimization with PDEs, Optimization under Uncertainty, Randomized Algorithms and Online Optimization, Combinatorial Optimization, Infinite-Dimensional Optimization 18 ECTS
Inverse Problems, Regularization Theory and Practice, Fast solvers for PDEs, Model Reduction, Fourier Analysis, Introduction to Wavelets, Analysis and Numerics of Integral Equations, Hilbert Space Methods, Boundary Integral Methods, Orthogonal Polynomials, Distributions and Differential Operators
Time Series Analysis, Quantitative Finance, Asymptotic and Extreme Value Statistics, Mathematical Methods of Uncertainty Quantification, Methods of Algebraic Statistics
Graph Theory, Singularity Theory, Game Theory, Mathematics of Big Data, Algebraic Geometry, Convex and Toric Geometry, Low-dimensional geometry and topology
3. to 4. sem. 3 Research Seminars and/or Summer schools 12 ECTS
3. to 4. sem. Master Thesis 30 ECTS
1. to 4. sem. Minor in
Mechanical Engineering, Electrical Engineering and Information Technology, Computer Science, Economics and Business Administration
A more detailed description of the content of each course offered within this program can be found here. 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.

Ph.D. program

Students with excellent results in their Master 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.
6. to 10. sem. Research for Ph.D. thesis
6. to 10. sem. Seminars, additional lectures