Preliminary course catalogue - changes and additions are likely.
Click on the course title for more information!
Precourse (for students in mathematics)
30.09.–02.10. and 04.10.; begins on 30.09. at 9h15 in HS Rundbau.
Language: in German
Precourse (for students in science and engineering)
02.10.–05.10.2024, begins at 9h in HS Rundbau.
Teacher: Susanne Knies
Language: in German
Exercising the Basics
Teacher: Fachschaft
Language: in German
Supervised Exercising
Teacher: Fachschaft
Language: in German
Analysis I
Lecture: Di, Mi, 8-10h, HS Rundbau, Albertstr. 21
Tutorial: 2 hours, various dates
Sir-in Exam: Date to be announced
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Teacher: Ernst Kuwert
Assistant: Xuwen Zhang
Language: in German
Analysis I is one of the two basic lectures in the mathematics course. It deals with concepts based on the notion of limit. The central topics are: induction, real and complex numbers, convergence of sequences and series, completeness, exponential function and trigonometric functions, continuity, derivation of functions of one variable and regulated integrals.
Required: High school mathematics. \ Attendance of the preliminary course (for students in mathematics) is recommended.
Analysis (2HfB21, BSc21, MEH21, MEB21)
Analysis I (BScInfo19, BScPhys20)
Linear Algebra I
Lecture: Mo, Do, 8-10h, HS Rundbau, Albertstr. 21
Tutorial: 2 hours, various dates
Sir-in Exam: Date to be announced
Teacher: Sebastian Goette
Assistant: Mikhail Tëmkin
Language: in German
Linear Algebra I is one of the two introductory lectures in the mathematics degree program that form the basis for further courses. Topics covered include: fundamental concepts (in particular fundamental concepts of set theory and equivalence relations), groups, fields, vector spaces over arbitrary fields, basis and dimension, linear mappings and transformation matrix, matrix calculus, linear systems of equations, Gaussian elimination, linear forms, dual space, quotient vector spaces and homomorphism theorem, determinant, eigenvalues, polynomials, characteristic polynomial, diagonalizability, affine spaces. The background to the mathematical content is explained in terms of ideas and the history of mathematics.
Required: High school mathematics. \ Attendance of the preliminary course (for students in mathematics) is recommended.
Linear Algebra (2HfB21, BSc21, MEH21)
Linear Algebra (MEB21)
Linear Algebra I (BScInfo19, BScPhys20)
Numerics I
Lecture: Mi, 14-16h, HS Weismann-Haus, Albertstr. 21a
Tutorial: 2 hours, every other week, various dates
Teacher: Patrick Dondl
Language: in German
Numerics is a sub-discipline of mathematics that deals with the practical solution of mathematical problems. As a rule, problems are not solved exactly but approximately, for which a sensible compromise between accuracy and computational effort must be found. The first part of the two-semester course focuses on questions of linear algebra such as solving linear systems of equations and determining the eigenvalues of a matrix. Attendance at the accompanying practical exercises ({\em Praktische Übung zur Numerik}) is recommended. These take place every 14 days, alternating with the lecture's tutorial.
Required: Linear Algebra~I \ Recommended: Linear Algebra~II and Analysis~I (required for Numerics~II)
Numerics (BSc21)
Numerics (2HfB21, MEH21)
Numerics I (MEB21)
Elementary Probability Theory I
Lecture: Fr, 10-12h, HS Weismann-Haus, Albertstr. 21a
Tutorial: 2 hours, every other week, various dates
Sir-in Exam: Date to be announced
Teacher: Thorsten Schmidt
Language: in German
Stochastic is, to put it loosely, the “mathematics of chance”, about which---possibly contrary to first impressions---many precise and not at all random statements can be formulated and proven. The aim of the lecture is to give an introduction to stochastic modeling, to explain some basic concepts and results of Stochastic and to illustrate them with examples. It is also intended as a motivating preparation for the lecture “Probability Theory” in the summer semester, especially for students in the B.Sc. in Mathematics. Topics covered include: Discrete and continuous random variables, probability spaces and measures, combinatorics, expected value, variance, correlation, generating functions, conditional probability, independence, weak law of large numbers, central limit theorem. The lecture Elementary Probability Theory~II in the summer semester will mainly be devoted to statistical topics. If you are interested in a practical, computer-supported implementation of individual lecture contents, participation in the regularly offered practical excercise “Praktischen Übung Stochastik" is also recommended (in parallel or subsequently).
Required: Linear Algebra~I, Analysis~I and II. \ Note that Linear Algebra~I can be attended in parallel.
Elementary Probabilty Theory (2HfB21, MEH21)
Elementary Probability Theory I (BSc21, MEB21, MEdual24)
Further Chapters in Analysis
Lecture: Mi, 8-10h, HS Weismann-Haus, Albertstr. 21a
Tutorial: 2 hours, various dates
Sir-in Exam: Date to be announced
Teacher: Ernst August v. Hammerstein
Language: in German
\textit{Multiple integration:} Jordan content in \(\mathbb R^n\), Fubini's theorem, transformation theorem, divergence and rotation of vector fields, path and surface integrals in \(\mathbb R^3\), Gauss' theorem, Stokes' theorem.\ \textit{Complex analysis:} Introduction to the theory of holomorphic functions, Cauchy's integral theorem, Cauchy's integral formula and applications.
Required: Analysis~I and II, Linear Algebra~I and II
Further Chapters in Analysis (MEd18, MEH21, MEdual24)
Basics in Applied Mathematics
Lecture: Di, Do, 10-12h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Computer exercise: 2 hours, date to be determined
Teacher: Sören Bartels, Moritz Diehl, Thorsten Schmidt
Language: in English
This course provides an introduction into the basic concepts, notions, definitions and results in probability theory, numerics and optimization, accompanied with programming projects in Python. Besides deepen mathematical skills in principle, the course lays the foundation of further classes in these three areas.
None that go beyond admission to the degree programme.
Basics in Applied Mathematics (MScData24)
Algebra and Number Theory
Lecture: Di, Do, 10-12h, HS Weismann-Haus, Albertstr. 21a
Tutorial: 2 hours, various dates
Sir-in Exam: Date to be announced
Teacher: Wolfgang Soergel
Assistant: Damian Sercombe
Language: in German
This lecture continues the linear algebra courses. It treats groups, rings, fields and applications in the number theory and geometry. The highlights of the lecture are the classification of finite fields, the impossibility of the trisection of angles with circle and ruler, the non-existence of a solution formula for the general equations of fifth degree and the quadratic reciprocity law.
Required: Linear Algebra~I and II
Algebra and Number Theory (2HfB21, MEH21)
Compulsory Elective in Mathematics (BSc21)
Introduction to Algebra and Number Theory (MEB21)
Algebra and Number Theory (MEdual24)
Pure Mathematics (MSc14)
Elective (MSc14)
Elective (MScData24)
Algebraic Topology
Lecture: Di, Do, 10-12h, SR 404, Ernst-Zermelo-Str. 1
Tutorial: 2 hours, date to be determined
Teacher: Maximilian Stegemeyer
Language: in German
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Mathematical Concentration (MEd18, MEH21)
Pure Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective (MScData24)
Analysis III
Lecture: Mo, Mi, 10-12h, HS Weismann-Haus, Albertstr. 21a
Tutorial: 2 hours, various dates
Sir-in Exam: Date to be announced
Teacher: Michael Růžička
Language: in German
Lebesgue measure and measure theory, Lebesgue integral on measure spaces and Fubini's theorem, Fourier series and Fourier transform, Hilbert spaces. Differential forms, their integration and outer derivative. Stokes' theorem and Gauss' theorem.
Required: Analysis I and II, Linear Algebra I
Elective (Option Area) (2HfB21)
Analysis III (BSc21)
Mathematical Concentration (MEd18, MEH21)
Elective in Data (MScData24)
Complex Analysis
Lecture: Di, Do, 8-10h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Teacher: Stefan Kebekus
Language: in German
Complex analysis deals with functions \(f : \mathbb C \to \mathbb C\) , which map complex numbers to complex numbers. Many concepts of Analysis~I can be directly transferred to this case, e.\,g. the definition of differentiability. One might expect that this would lead to a theory analogous to Analysis~I but much more is true: in many respects you get a more elegant and simpler theory. For example, complex differentiability on an open set implies that a function is even infinitely often differentiable, and this is further consistent with analyticity. For real functions, all these notions are different. However, some new ideas are also necessary: For real numbers \(a\), \(b\) one integrates for \[\int_a^b f(x) \mathrm dx\] over the elements of the interval \([a, b]\) or \([b, a]\). However, if \(a\), \(b\) are complex numbers, it is no longer so clear clear how such an integral is to be calculated. One could, for example, in the complex numbers along the line that connects \(a, b \in \mathbb C\), or along another curve that leads from \(a\) to \(b\). Does this lead to a well-defined integral term or does such a curve integral depend on the choice of the curve?
Required: Analysis I+II, Linear Algebra I
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Mathematical Concentration (MEd18, MEH21)
Pure Mathematics (MSc14)
Elective (MSc14)
Elective (MScData24)
Introduction to Theory and Numerics of Partial Differential Equations
Lecture: Mo, Mi, 12-14h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Teacher: Patrick Dondl
Language: in English
The aim of this course is to give an introduction into theory of linear partial differential equations and their finite difference as well as finite element approximations. Finite element methods for approximating partial differential equations have reached a high degree of maturity, and are an indispensable tool in science and technology. We provide an introduction to the construction, analysis, and implementation of finite element methods for different model problems. We will address elementary properties of linear partial differential equations along with their basic numerical approximation, the functional-analytical framework for rigorously establishing existence of solutions, and the construction and analysis of basic finite element methods.
Required: Analysis~I and II, Linear Algebra~I and II as well as knowledge about higher-dimensional integration (e.g. from Analysis~III or Extensions of Analysis) \ Recommended: Numerics for differential equations, Functional analysis
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Mathematical Concentration (MEd18, MEH21)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Advanced Lecture in Numerics (MScData24)
Elective in Data (MScData24)
Mathematical Statistics
Lecture: Di, Do, 14-16h, SR 404, Ernst-Zermelo-Str. 1
Tutorial: 2 hours, date to be determined
Teacher: Ernst August v. Hammerstein
Language: in English
The lecture builds on basic knowledge about Probability Theory. The fundamental problem of statistics is to infer from a sample of observations as precise as possible statements about the data-generating process or the underlying distributions of the data. For this purpose, the most important methods from statistical decision theory such as test and estimation methods are introduced in the lecture. \\ Key words hereto include Bayes estimators and tests, Neyman-Pearson test theory, maximum likelihood estimators, UMVU estimators, exponential families, linear models. Other topics include ordering principles for reducing the complexity of models (sufficiency and invariance). Statistical methods and procedures are used not only in the natural sciences and medicine, but in almost all areas in which data is collected and analyzed This includes, for example, economics (“econometrics”) and the social sciences (especially psychology). However, in the context of this lecture, we will focus less on applications, but---as the name suggests---more on the mathematical justification of the methods.
Required: Probability Theory (in particular measure theory and conditional probabilities/expectations)
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Advanced Lecture in Stochastics (MScData24)
Elective in Data (MScData24)
Model Theory
Lecture: Di, Do, 12-14h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Amador Martín Pizarro
Assistant: Charlotte Bartnick
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Pure Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective (MScData24)
Probabilistic Machine Learning
Lecture: Di, Do, 12-14h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Teacher: Giuseppe Genovese
Assistant: Sebastian Stroppel
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Advanced Lecture in Stochastics (MScData24)
Elective in Data (MScData24)
Probability Theory II – Stochastic Processes
Lecture: Mo, Mi, 14-16h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Teacher: Angelika Rohde
Language: in English
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Advanced Lecture in Stochastics (MScData24)
Elective in Data (MScData24)
Calculus of Variations
Lecture: Mo, Mi, 10-12h, HS II, Albertstr. 23b
Tutorial: 2 hours, date to be determined
Teacher: Guofang Wang
Assistant: Florian Johne
Language: in German
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Mathematical Concentration (MEd18, MEH21)
Pure Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective (MScData24)
Reading courses
Teacher: All professors and 'Privatdozenten' of the Mathematical Institute
Language: Talk/participation possible in German and English
In a reading course, the material of a four-hour lecture is studied in supervised self-study. In rare cases, this may take place as part of a course; however, reading courses are not usually listed in the course catalog. If you are interested, please contact a professor or a private lecturer before the start of the course; typically, this will be the supervisor of your Master's thesis, as the reading course ideally serves as preparation for the Master's thesis (both in the M.Sc. and the M.Ed. programs).
The content of the reading course, the specific details, and the coursework requirements will be determined by the supervisor at the beginning of the lecture period. The workload should be equivalent to that of a four-hour lecture with exercises.
Reading Course (MEd18, MEH21)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Futures and Options
Lecture: Mo, 10-12h, -, -
Exercise session: Di, 8-10h, -, -
Teacher: Eva Lütkebohmert-Holtz
Language: in English
This course covers an introduction to financial markets and products. Besides futures and standard put and call options of European and American type we also discuss interest-rate sensitive instruments such as swaps.
For the valuation of financial derivatives we first introduce financial models in discrete time as the Cox--Ross--Rubinstein model and explain basic principles of risk-neutral valuation. Finally, we will discuss the famous Black--Scholes model which represents a continuous time model for option pricing.
Required: Elementary Probability Theory~I
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Machine Learning and Mathematical Logic
Lecture: Do, 14-16h, SR 226, Hermann-Herder-Str. 10
Tutorial: 2 hours, date to be determined
Teacher: Maxwell Levine
Language: in English
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Pure Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Markov Chains
Lecture: Mi, 10-12h, SR 226, Hermann-Herder-Str. 10
Tutorial: 2 hours, date to be determined
Teacher: David Criens
Language: in English
The class of Markov chains is an important class of (discrete-time) stochastic processes that are used frequently to model for example the spread of infections, queuing systems or switches of economic scenarios. Their main characteristic is the Markov property, which roughly means that the future depends on the past only through the current state. In this lecture we provide the mathematical foundation of the theory of Markov chains. In particular, we learn about path properties, such as recurrence and transience, state classifications and discuss convergence to the equilibrium. We also study extensions to continuous time. On the way we discuss applications to biology, queuing systems and resource management. If the time allows, we also take a look at Markov chains with random transition probabilities, so-called random walks in random environment, which is a prominent model in the field of random media.
Required: Elementary Probability Theory~I \ Recommended: Analysis~III, Probability Theory~I
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Measure Theory
Teacher: Peter Pfaffelhuber
Assistant: Samuel Adeosun
Language: in English
Measure Theory is the foundation of advanced probability theory. In this course, we build on knowledge in analysis and provide all necessary results for later classes in statistics, probabilistic machine learning and stochastic processes. It contains set systems, constructions of measures using outer measures, the integral, and product measures.
Required: Basic courses in analysis, and an understanding of mathematical proofs.
Elective in Data (MScData24)
Mathematical Introduction to Deep Neural Networks
Lecture: Mi, 12-14h, SR 226, Hermann-Herder-Str. 10
Tutorial: 2 hours, date to be determined
Teacher: Diyora Salimova
Language: in English
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Numerical Optimal Control
Tutorial / flipped classroom: Di, 14-16h, HS II, Albertstr. 23b
Teacher: Moritz Diehl
Language: in English
The aim of the course is to give an introduction to numerical methods for the solution of optimal control problems in science and engineering. The focus is on both discrete time and continuous time optimal control in continuous state spaces. It is intended for a mixed audience of students from mathematics, engineering and computer science.
The course covers the following topics:
The lecture is accompanied by intensive weekly computer exercises offered both in MATLAB and Python (6~ECTS) and an optional project (3~ECTS). The project consists in the formulation and implementation of a self-chosen optimal control problem and numerical solution method, resulting in documented computer code, a project report, and a public presentation.
Required: Analysis~I and II, Linear Algebra~I and II \ Recommended: Numerics I, Ordinary Differential Equations, Numerical Optimization
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Theory and Numerics for Partial Differential Equations – ??
Lecture: Mo, 12-14h, SR 226, Hermann-Herder-Str. 10
Tutorial: 2 hours, date to be determined
Teacher: Sören Bartels
Language: in English
Elective (Option Area) (2HfB21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Applied Mathematics (MSc14)
Mathematics (MSc14)
Concentration Module (MSc14)
Elective (MSc14)
Elective in Data (MScData24)
Introduction to Mathematics Education
Mo, 10-12h, SR 226, Hermann-Herder-Str. 10
Tutorial: 2 hours, date to be determined
Sir-in Exam: Date to be announced
Teacher: Katharina Böcherer-Linder
Language: in German
Mathematics didactic principles and their learning theory foundations and possibilities of teaching implementation (also e.g. with the help of digital media). \\ Theoretical concepts on central mathematical thinking activities such as concept formation, modeling, problem solving and reasoning. \\ Mathematics didactic constructs: Barriers to understanding, pre-concepts, basic ideas, specific difficulties with selected mathematical content. \\ Concepts for dealing with heterogeneity, taking into account subject-specific characteristics particularities (e.g. dyscalculia or mathematical giftedness).\\ Levels of conceptual rigour and formalization as well as their age-appropriate implementation.
Required: Analysis~I, Linear Algebra~I
(Introduction to) Mathematics Education (2HfB21, MEH21, MEB21)
Introduction to Mathematics Education (MEdual24)
Mathematics Education ‒ Functions and Analysis
Do, 9-12h, SR 226, Hermann-Herder-Str. 10
Teacher: Katharina Böcherer-Linder
Language: in German
Exemplary implementations of the theoretical concepts of central mathematical thought processes such as concept formation, modeling, problem solving and reasoning for the content areas of functions and analysis. \\ Barriers to understanding, pre-concepts, basic ideas, specific difficulties for the content areas of functions and analysis. \\ Fundamental possibilities and limitations of media, in particular of computer-aided mathematical tools mathematical tools and their application for the content areas of functions and analysis. Analysis of individual mathematical learning processes and errors as well as development individual support measures for the content areas of functions and analysis.
Required: Introduction to Mathematics Education, Knowledge about analysis and numerics
Mathematics Education for Specific Areas of Mathematics (MEd18, MEH21, MEB21)
Mathematics Education ‒ Probability Theory and Algebra
Mi, 11-14h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Frank Reinhold
Language: in German
Exemplary implementations of the theoretical concepts of central mathematical thought processes such as concept formation, modeling, problem solving and reasoning for the content areas of stochastics and algebra. \\ Barriers to understanding, pre-concepts, basic ideas, specific difficulties for the content areas of stochastics and algebra.\ Basic possibilities and limitations of media, especially computer-based mathematical tools and their mathematical tools and their application for the content areas of stochastics and algebra. and algebra. \\ Analysis of individual mathematical learning processes and errors as well as development individual support measures for the content areas of stochastics and algebra.
Required: Introduction to Mathematics Education, knowledge from stochastics and algebra.
Mathematics Education for Specific Areas of Mathematics (MEd18, MEH21, MEB21)
Mathematics education seminar: Media Use in Teaching Mathematics
Seminar: Mi, 15-18h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Jürgen Kury
The use of teaching media in mathematics lessons wins both at the level of lesson planning and lesson realization in importance. Against the background of constructivist learning theories shows that the reflective use of computer programs, among other things mathematical concept formation in the long term. For example experimenting with computer programs allows mathematical structures to be discovered, without this being overshadowed by individual routine operations (such as term transformation) would be covered up. This has far-reaching consequences for mathematics lessons. For this reason, this seminar aims to provide students the necessary decision-making and action skills to prepare future mathematics teachers for their professional activities. Starting from initial considerations about lesson planning, computers and tablets with regard to their respective didactic potential and tested with learners during a classroom visit. The exemplary systems presented are:
The students should develop teaching sequences, which will then be tested and reflected on with pupils (where this will be possible).
Recommended: Basic courses in mathematics
Supplementary Module in Mathematics Education (MEd18, MEH21, MEB21)
Mathematics education seminars at Freiburg University of Education
Teacher: Lecturers of the University of Education Freiburg
Language: in German
Supplementary Module in Mathematics Education (MEd18, MEH21, MEB21)
Module "Research in Mathematics Education"
Part 1: Seminar 'Development Research in Mathematics Education ‒ Selected Topics': Mo, 14-16h, Raum noch nicht bekannt, PH Freiburg
Part 2: Seminar 'Research Methods in Mathematics Education': Mo, 16-19h, Raum noch nicht bekannt, PH Freiburg
Part 3: Master's thesis seminar: Development and Optimisation of a Research Project in Mathematics Education
Registration: see course descriptions
Teacher: Lecturers of the University of Education Freiburg
Language: in German
The three related courses of the module prepare students for an empirical Master thesis in mathematics didactics. The course is jointly designed by all professors at the PH with mathematics didactics research projects at secondary levels 1 and 2 and is carried out by one of these researchers. Afterwards, students have the opportunity to start Master thesis with one of these supervisors - usually integrated into larger ongoing research projects.
The first course of the module provides an introduction to strategies of empirical didactic research (research questions, research status, research designs). Students deepen their skills in scientific research and the evaluation of subject-specific didactic research. In the second course (in the last third of the semester) students are introduced to central qualitative and quantitative research methods through concrete work with existing data (interviews, student products, experimental data), students are introduced to central qualitative and quantitative research methods. The third course is an accompanying seminar for the Master thesis.
The main objectives of the module are the ability to receive mathematics didactic research in order to didactic research to clarify questions of practical relevance and to plan an empirical mathematics didactics Master thesis. It will be held as a mixture of seminar, development of research topics in groups and active work with research data. Recommended literature will be depending on the research topics offered within the respective courses. The parts can also be attended in different semesters, for example part~1 in the second Master semester and part~2 in the compact phase of the third Master semester after the practical semester.
Research in Mathematics Education (MEd18, MEH21, MEB21)
Learning by Teaching
Organisation: Susanne Knies
Language: in German
What characterizes a good tutorial? This question will be discussed in the first workshop and tips and suggestions will be given. Experiences will be shared in the second workshop.
Elective (Option Area) (2HfB21)
Elective (BSc21)
Elective (MSc14)
Elective (MScData24)
Supplementary Module in Mathematics (MEd18)
SAALA
Mo, 14-16h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Katharina Böcherer-Linder, Markus Junker
Supplementary Module in Mathematics (MEd18)
High-school Oriented Aspects of Analysis and Linear Algebra (MEdual24)
Computer exercises for 'Introduction to Theory and Numerics of Partial Differential Equations'
Teacher: Patrick Dondl
Language: in English
Elective (Option Area) (2HfB21)
Elective (BSc21)
Supplementary Module in Mathematics (MEd18)
Elective (MSc14)
Elective (MScData24)
Computer exercises in Numerics
Teacher: Patrick Dondl
Language: in German
Computer Exercise (2HfB21, MEH21, MEB21)
Elective (Option Area) (2HfB21)
Numerics (BSc21)
Supplementary Module in Mathematics (MEd18)
Computer exercises for 'Theory and Numerics of Partial Differential Equations'
Teacher: Sören Bartels
Language: in English
Elective (Option Area) (2HfB21)
Elective (BSc21)
Supplementary Module in Mathematics (MEd18)
Elective (MSc14)
Elective (MScData24)
Please note the registration modalities for the individual proseminars published in the comments to the course catalog: As a rule, places are allocated after pre-registration by e-mail at the preliminary meeting at the end of the lecture period of the summer semester. You must then register online for the examination; the registration period runs from August 1, 2025 to October 8, 2025; if you would like to attend a proseminar but have not been allocated a place, please contact the degree program coordinator immediately.
Undergraduate seminar: Elementary Number Theory
Seminar: Mi, 8-10h, SR 404, Ernst-Zermelo-Str. 1
Preregistration:
Preliminary Meeting
Preparation meetings for talks: Dates by arrangement
Teacher: Annette Huber-Klawitter
Assistant: Christoph Brackenhofer
Undergraduate Seminar (2HfB21, BSc21, MEH21, MEB21)
Undergraduate seminar: Ordinary Differential Equations
Seminar: Mi, 14-16h, SR 226, Hermann-Herder-Str. 10
Preregistration:
Preliminary Meeting
Preparation meetings for talks: Dates by arrangement
Teacher: Diyora Salimova
Undergraduate Seminar (2HfB21, BSc21, MEH21, MEB21)
Undergraduate seminar: Graph Theroy
Seminar: Di, 16-18h, SR 127, Ernst-Zermelo-Str. 1
Preregistration:
Preliminary Meeting
Preparation meetings for talks: Dates by arrangement
Teacher: Heike Mildenberger
Undergraduate Seminar (2HfB21, BSc21, MEH21, MEB21)
Seminar
Teacher: Susanne Knies
Undergraduate Seminar (2HfB21, BSc21, MEH21, MEB21)
Supplementary Module in Mathematics (MEd18)
Please note the registration modalities for the individual seminars published in the comments to the course catalog: As a rule, places are allocated after pre-registration by e-mail at the preliminary meeting at the end of the lecture period of the summer semester. You must then register online for the exam; the registration period runs from August 1, 2025 to October 8, 2025.
M.Ed.-Seminar (nach Praxissemester)
Teacher: Susanne Knies
Assistant: Jonah Reuß
Undergraduate Seminar (2HfB21, BSc21, MEH21, MEB21)
Supplementary Module in Mathematics (MEd18)
Seminar: Computational PDEs
Seminar: Mo, 14-16h, SR 226, Hermann-Herder-Str. 10
Preregistration:
Preliminary Meeting
Preparation meetings for talks: Dates by arrangement
Teacher: Sören Bartels
The seminar will cover advanced topics in the theory and numerics of partial differential equations. This includes the iterative solution of the resulting linear systems of equations with multigrid and domain decomposition methods, the adaptive refinement of finite element grids, the derivation of an approximation theory with explicit constants, and the solution of nonlinear problems.
Introduction to Theory and Numerics of Partial Differential Equations
Elective (Option Area) (2HfB21)
Mathematical Seminar (BSc21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Mathematical Seminar (MSc14)
Elective (MSc14)
Mathematical Seminar (MScData24)
Elective in Data (MScData24)
Seminar: Medical Data Science
Seminar: Mi, 10:15-11:30h, HS Medizinische Biometrie, 1. OG, Stefan-Meier-Str. 26
Preregistration:
Preliminary Meeting 17.07., HS Medizinische Biometrie, 1. OG, Stefan-Meier-Str. 26
Teacher: Harald Binder
Language: Talk/participation possible in German and English
To answer complex biomedical questions from large amounts of data, a wide range of analysis tools is often necessary, e.g. deep learning or general machine learning techniques, which is often summarized under the term ``Medical Data Science''. Statistical approaches play an important rôle as the basis for this. A selection of approaches is to be presented in the seminar lectures that are based on recent original work. The exact thematic orientation is still to be determined.
Good knowledge of probability theory and mathematical statistics.
Elective (Option Area) (2HfB21)
Mathematical Seminar (BSc21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Mathematical Seminar (MSc14)
Elective (MSc14)
Mathematical Seminar (MScData24)
Elective in Data (MScData24)
Seminar: Minimal Surfaces
Seminar: Mi, 16-18h, SR 125, Ernst-Zermelo-Str. 1
Preregistration:
Preliminary Meeting
Preparation meetings for talks: Dates by arrangement
Teacher: Guofang Wang
Elective (Option Area) (2HfB21)
Mathematical Seminar (BSc21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Mathematical Seminar (MSc14)
Elective (MSc14)
Elective (MScData24)
Seminar
Seminar: Di, 14-16h, SR 125, Ernst-Zermelo-Str. 1
Teacher: Wolfgang Soergel
Assistant: Damian Sercombe
Elective (Option Area) (2HfB21)
Mathematical Seminar (BSc21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Mathematical Seminar (MSc14)
Elective (MSc14)
Elective (MScData24)
Seminar
Seminar: Mo, 16-18h, SR 127, Ernst-Zermelo-Str. 1
Teacher: Angelika Rohde
Elective (Option Area) (2HfB21)
Mathematical Seminar (BSc21)
Compulsory Elective in Mathematics (BSc21)
Supplementary Module in Mathematics (MEd18)
Mathematical Seminar (MSc14)
Elective (MSc14)
Mathematical Seminar (MScData24)
Elective in Data (MScData24)
Graduate Student Speaker Series
Mi, 14-16h, SR 127, Ernst-Zermelo-Str. 1
Organisation: Sören Bartels, Ernst August v. Hammerstein
In the Graduate Student Speaker Series, students of the M.Sc. degreee programme ‘Mathematics in Data and Technology’ talk about their Master's thesis or their programming projects, and the lecturers of the programme talk about their fields of work.
Graduate Student Speaker Series (MScData24)
Within the EUCOR cooperation, you can attend courses at the partner universities. If you click on the universities, you will find links to their course catalogues.
University of Basel
general course catalogue, see https://vorlesungsverzeichnis.unibas.ch/de/semester-planung
Karlsruhe Institute for Technology
course catalogue for mathematics see https://www.math.kit.edu/vvz
University of Strasbourg
Master Mathématiques Fondamentales et Appliquées see https://irma.math.unistra.fr/linstitut/lmd_enseignement.html#masters
Service Teaching is specifically for students of subjects other than mathematics and not intended for the mathematics degree programmes.
Logic for Computer Science Students
Lecture: Mi, 10-12h, HS 00-026, Georges-Köhler-Allee 101
Tutorial: 2 hours, various dates
Teacher: Heike Mildenberger
Language: in German
Logic for Philosophy Students
Lecture: Mi, 10-12h, -, -
Tutorial: 2 hours, various dates
Teacher: Markus Junker
Assistant: Stefan Ludwig
Language: in German
Mathematical Methods for Economics and Finance
Lecture: Di, 10-12h, -, -
Exercise session: Fr, 10-12h, -, -
Teacher: Ernst August v. Hammerstein
Language: in English
Mathematics I for Computer Science and Engineering Students
Lecture: Mo, Di, 12-14h, HS Rundbau, Albertstr. 21
Tutorial: 2 hours, various dates
Teacher: Peter Pfaffelhuber
Language: in German
Mathematics I for Science Students
Lecture: Mo, 14-16h, HS Rundbau, Albertstr. 21, Fr, 8-10h, HS Rundbau, Albertstr. 21
Tutorial: 2 hours, various dates
Teacher: Susanne Knies
Assistant: Ben Snodgrass
Language: in German
Working group seminar: Geometrical Analysis
Di, 16-18h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Ernst Kuwert, Guofang Wang
Language: Talk/participation possible in German and English
Working group seminar: Non-Newtonian Fluids
Fr, 10-12h, SR 127, Ernst-Zermelo-Str. 1
Teacher: Michael Růžička
Language: Talk/participation possible in German and English
Research seminar: Algebra, Number Theory, and Algebraic Geometry
Fr, 10-12h, SR 404, Ernst-Zermelo-Str. 1
Organisation: Annette Huber-Klawitter, Stefan Kebekus, Abhishek Oswal, Wolfgang Soergel
Language: Talk/participation possible in German and English
The research seminar consists of research talks from the respective specialisation area. The single talks are usually announced in the weekly programme and on the homepage.
Research seminar: Applied Mathematics
Di, 14-16h, SR 226, Hermann-Herder-Str. 10
Organisation: Sören Bartels, Patrick Dondl, Michael Růžička, Diyora Salimova
Language: Talk/participation possible in German and English
The research seminar consists of research talks from the respective specialisation area. The single talks are usually announced in the weekly programme and on the homepage.
Research seminar: Differential Geometry
Mo, 16-18h, SR 404, Ernst-Zermelo-Str. 1
Organisation: Sebastian Goette
Language: Talk/participation possible in German and English
The research seminar consists of research talks from the respective specialisation area. The single talks are usually announced in the weekly programme and on the homepage.
Research seminar: Mathematical Logic
Di, 14-16h, SR 404, Ernst-Zermelo-Str. 1
Organisation: Amador Martín Pizarro, Heike Mildenberger
Language: Talk/participation possible in German and English
The research seminar consists of research talks from the respective specialisation area. The single talks are usually announced in the weekly programme and on the homepage.
Research seminar: Medical Statistics
Mi, 13-14h, HS Medizinische Biometrie, 1. OG, Stefan-Meier-Str. 26
Organisation: Harald Binder
Language: Talk/participation possible in German and English
Research seminar: Probability Theory
Mi, 16-17h, SR 226, Hermann-Herder-Str. 10
Organisation: David Criens, Peter Pfaffelhuber, Angelika Rohde, Thorsten Schmidt
Language: Talk/participation possible in German and English
The research seminar consists of research talks from the respective specialisation area. The single talks are usually announced in the weekly programme and on the homepage.
Mathematics Education Colloquium
Di, 18:30-20h, HS II, Albertstr. 23b
Teacher: Various speakers
Organisation: Katharina Böcherer-Linder, Ernst Kuwert
Language: in German
The Mathematics Education Colloquium aims to show concrete examples, to further develop existing concepts and to encourage didactic experimentation. It is aimed at teachers of all school types, students, trainee teachers and anyone interested.
Mathematical Colloquium
Do, 15-16h, HS II, Albertstr. 23b
Teacher: Various speakers
Organisation: Amador Martín Pizarro
Language: Talk/participation possible in German and English
Colloquium for Mathematics Students
Do, 14-15h, HS II, Albertstr. 23b
Teacher: Various speakers
Organisation: Annette Huber-Klawitter, Markus Junker, Amador Martín Pizarro
Language: Talk/participation possible in German and English
In the ‘Mathematical Colloquium for Students’, topics from the various fields of work are presented in a ‘mathematically understandable’ way. The lectures are aimed at advanced Bachelor's students, Master's students of all specialisations, as well as doctoral students. Afterwards, there will be an opportunity for questions, discussion and dialogue over coffee and tea.
Seminar on Data Analysis and Modelling
Fr, 12-13h, SR 404, Ernst-Zermelo-Str. 1
Teacher: Various speakers
Organisation: Harald Binder, Peter Pfaffelhuber, Angelika Rohde, Thorsten Schmidt, Jens Timmer
Language: Talk/participation possible in German and English
Current, interdisciplinary research is presented here, in which mathematical models enable the understanding of natural and social science issues.