Answers to questions concerning the organisation of studies (registration for courses, pass/fail assessments and exams, detailed plan of modules etc) can be found on the web pages of the examination office. Some questions may alternatively be answered in the FAQ. For further inquiries you can contact the student counseling of the Mathematical Institute ( ).
You need a Bachelor's degree with a minimum of 30 credits in Mathematics, including 12 credits in foundations of calculus and linear algebra. In english, you must have B2. You can only start this program in the winter term (October 1st).
> We believe that mathemtics is the foundation of data science and technology, and this program provides the mathematical foundations of artificial intelligence and machine learning. All necessary skills such as numerical mathematics, optimization, and probability theory are covered in various courses which are based on basic skills in calculus and linear algebra.
Applications of mathematics often require the knowledge to convert project results into applicable software. Although programming skills are not required upon admission, coding will be an important part of the basic module, and will be strengthened in a specific coding module.
The programming project can be exchanged by an industrial placement (interneship) of at least six weeks. As examples, we have connections to various local companies, including Sick, Baloise, LBBW, Allianz, Fraunhofer, Bosch.
There are no special fees for the master course itself, one only has to pay a general semester fee (currently about € 180,-). Students from a non-EU country additionally have to pay a fee of € 1500,- per term. For more detailed information, see here.
Freiburg is a green city close to the Black Forest with many opportunities for outdoor activities. The University of Freiburg has not only has a long tradition in all areas of the natural sciences and humanities, but is also very active in research, as its rankings show. The mathematical institute, which hosts the largest part of this program, covers a broad spectrum of topics, from mathematical logic to machine learning.
You will obtain solid foundation in mathematics in a basic course, and an additional advanced course in applied mathematics. In the electives, you can choose from modules such as numerical optimization, numerics for partial differential equations, neural nets, financial mathematics, dynamical systems in biology, econometrics, computer vision, automated machine learning, etc. More information can be found here
Precise regulations can be found in the legally binding admission regulations. We summarize the admission requirements here:
(1) A degree acknowledged in Germany Bachelor's degree in mathematics, computer science, a natural science or engineering subject or an equivalent degree that fulfills the following conditions:(2) Language skills: Level B2 in English ( Accepted certificates )
Applications start April 15 and end September 15. (A start is only possible in
winter semester, which starts in October).
Applications received by May 15 will be notified by the end of May.
All documents can be found here.
These regulations govern the application procedure, such as described above.
The choices you have in the modules are described semester by semester in the current supplements to the module handbooks. Compact information can be found in the usability tables.
This program comprises 120 ECTS credits (standard for programs in 4 semesters) and is divided into the following parts into the following parts:
This plan is only a guide! There are no rules which courses are to be taken in which semester, apart from the admission criteria for the Master's thesis (60 credits acquired before starting the thesis). Of course, there might be knowledge requirements for the selected courses courses.
sem |
Mathematics +
Programming Project
(27 credits Mathematics + 34 credits Master Thesis incl. Student Speaker Series + 9 credits Programming Project ) |
Electives in Data and Electives
(30-48 credits Electives in Data) (0-18 credits Electives) |
||
4 | Master's thesis |
Graduate Student Speaker Series |
||
3 | Seminar | Electives in Data | Electives | |
2 |
Programming Project/ Industrial Placement |
Graduate Student Speaker Series |
Electives in Data | Electives |
1 |
Basics in Applied
Mathematics |
Advanced Lecture in Numerics/Stochastics |
Electives in Data |
Legend | |||||
credits | = | ECTS-credits | sem | = | Semester |
= | Mandatory Courses without option | = | Master Thesis | ||
= | Mandatory Courses with options | = | Programming Project or Industrial Placement | ||
= | Courses with options, only coursework |