The course of study comprises 20 modules. Each semester, you will earn 20 ECTS points (credits), divided between 2-3 modules. The proseminar courses are an important and integral part of the curriculum. Thus, the B Sc in Mathematics degree encompasses 180 ECTS points.
The course takes an average of 4½ years.

In our experience, studying mathematics takes time and patience, as new mathematical concepts have to be learnt, practised and mastered. The time and commitment required to follow a mathematics course should not be underestimated and is usually around 30 hours per week.

Our bridging course and the way we design our modules are intended to (re)introduce you to the subject matter and make the best use of your weekly study time.

Mandatory modules

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 1
Description

Students will acquire basic competences in algorithmically oriented mathematics.

• Basics – Sets, Functions, Numbers, Absolute Value and Matlab I

• Induction, Relations and Matlab II

• Groups, Construction of Z, Minimum and Maximum and Matlab III

• Floating-Point Representation, Cancellation of Leading Digits and b-adic Representation

• Practical Floating-Point system

• Condition Number and Landau Symbol

• Polynomial interpolation

• Divided differences

• Linear systems and Gaußian elimination

• LU-decomposition and Matrix norms

• Stability of Gaußian elimination

• Symmetry and Cholesky

• Linear independence and Orthogonality

• Cubic Splines

• Approximation and Normal equations

Reading recommendations

Mandatory literature:

• Class script

Additional literature/special activities:

The most fitting literature is the following: www.schulthess.com/buchshop/detail/ISBN-9783642419515/Harbrecht-Helmut-Multerer-Michael/Algorithmische-Mathematik, but it is currently only available in German. A translation into English is planned in the future. The class script, provided in English, will cover the necessary content for this class.

• Otto Forster, Analysis I

• Gilbert Strang, Linear Algebra

• Herbert Amann and Joachim Escher, Analysis I

• Stephen Abbott, Understanding Analysis (Second Edition)

• Kenneth A. Ross, Elementary Analysis (Second Edition)

• H.-D. Ebbinghaus, Numbers

• Walter Rudin, Principles of Mathematical Analysis (Third Edition)

• Allen B. Downey, Think Python (Second Edition)

• Timothy Sauer, Numerical Analysis (Second Edition)

• Matlab (officially supported) or Octave

• Tablet for writing (e.g., HP Envy, Lenovo Yoga , Microsoft Surface, Wacom Intuos, Samsung Galaxy Tab, iPad, etc.)

(Stand FS23)

Lecturer

Prof. Dr Rolf Krause
Prof. Dr Rolf Krause

Assistants

Dr Patrick Zulian
MSc Samuel Cruz
MSc Samuel Cruz

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 1
Description

Students acquire basic competences in discrete structures, probability theory and basic statistics. The topics are

• Logic and Sets

• Sorting algorithms and complexity

• Graphs and trees

• Graph colouring and algorithms on graphs

• Probability spaces and probability

• Conditional probability and independency

• Random variables and discrete distributions

• Expectation and variance

• Elementary statistics

• Random number generators and simulation

Reading recommendations

Mandatory literature:

• Class script

Additional literature/special activities:

• H. Harbrecht and M. Multerer, Algorithmische Mathematik. Graphen, Numerik und Probabilistik, Springer

• B. Korte and C. Vygen, Combinatorial Optimization, Springer

• U. Krengel, Einführung in die Wahrscheinlichkeitstheorie und Statistik, Vieweg

(Stand FS23)

Lecturer

Prof. Dr Helmut Harbrecht
Prof. Dr Helmut Harbrecht

Assistants

BSc Ilja Kalmykov
BSc Ilja Kalmykov

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 2
Description

The student learns the basics of one-dimensional calculus.

Content:

• construction of the real numbers,

• sequences (convergence and convergence criteria),

• series (convergence and convergence criteria),

• functions of one real variable,

• continuity, uniform and Lipschitz continuity,

• complex numbers,

• function types: exponential, logarithm, sine, cosine, …

• differentiability and differentiation, differentiation rules,

• introductory examples for an ordinary differential equation (exp(x)),

• Taylor’s theorem,

• Riemann-Integral, fundamental theorem of calculus,

• function sequences, uniform convergence.

Reading recommendations

Mandatory literature:

Lecture notes provided by the lecturer.

Additional literature/special activities:

Books mentioned in the lecture notes.

(FS23)

Professor

Prof. Dr Matthias Voigt
Prof. Dr Matthias Voigt

Assistants

Dr Nikolaos Tsipinakis
Dr Nikolaos Tsipinakis
MSc Andrea Angino

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 2
Description

Students acquire basic competences in linear algebra:

• Fields and complex numbers

• Matrices and vectors

• Matrix products

• Subspaces

• Linear independence and bases

• Dimension

• Matrices and linear maps

• Change of basis

• Determinants (characterization, existence, properties, permutations)

• Endomorphisms (trace, eigenvalues and eigenvectors)

• Affine spaces and quotient vector spaces

Reading recommendations

Mandatory literature:

• Course Lecture Notes (available on Moodle)

Additional literature/special activities:

• M. Artin, Algebra

• G. Strang, Introduction to Linear Algebra

(FS23)

Professor

Prof. Dr Thomas Mettler
Prof. Dr Thomas Mettler

Assistants

Dr Keegan Jonathan Flood

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 3
Description

The student learns how to differentiate and integrate functions in several variables.

Content:

• Normed, metric, and topological spaces,

• convergence in metric spaces,

• closedness, compactness, connectness,

• differentiability and differentiation of functions in several variables,

• classical differential operators (nabla, rot, curl),

• inverse and implicit function theorem,

• measure theory,

• Lebesgue integration and L^p spaces,

• Theorems of Tonelli and Fubini

Reading recommendations

Mandatory literature:

Lecture notes provided by the lecturer.

Additional literature/special activities:

Books mentioned in the lecture notes.

(Stand FS23)

Professor

Prof. Dr Matthias Voigt
Prof. Dr Matthias Voigt

Assistants

Dr Nikolaos Tsipinakis
Dr Nikolaos Tsipinakis
MSc Andrea Angino

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semester 3
Description

Students acquire basic competences in linear algebra:

• Symmetry and groups

• Bilinear forms

• Euclidean spaces

• orthonormal bases

• Self adjoint endomorphism

• Quadratic forms

• Unitary spaces

• Jordan normal form

• Duality

Reading recommendations

Mandatory literature:

• Course Lecture Notes (available on Moodle)

Additional literature/special activities:

• M. Artin, Algebra

• G. Strang, Introduction to Linear Algebra

(FS23)

Professor

Prof. Dr Thomas Mettler
Prof. Dr Thomas Mettler

Assistants

Dr Micha Wasem
Dr Micha Wasem

ECTS8
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 4 and 5
Description

Description: This lecture gives an introduction into function theory and functional analysis

Content: Function theory: analytical functions, Cauchy’s integral theorem, properties of analytical functions, singu-larities, residue theorem Functional analysis: normed pscaes, dual, bounded and linear mappings (functionals), fixed point theorems, Hahn-Banach, Reflexivity, Hilbertspaces, Orthonormalbases and Fourier series, Theorem of Riesz, Lax-Milgram, adjoint operators, compact operators.

Lecturer

Prof. Dr Michel Chipot

ECTS6
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 4 and 5
Description

Description: This lecture gives an introduction to the mathematical theorey of stochastics

Content: Probability measures, probability spaces, random variables, distributions (normal, hypergeometric, Poissson, ...), density, Chebycheff, expectation, variance, moments, correlation, central limit theorem, Monte-Carlo methods, Markov-chains.

Lecturer

Prof. Antti Knowles

ECTS6
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 4 and 5
Description

Description: This lecture introduces fundamental numerical methods

Content: Condition number, Interpolation, approximation, direct solution methods, matrix factorization, singular value decomposition, adaptivity.

Lecturer

Dr Marco Favino

ECTS8
Repetition of Modulespring semester
Target AudienceStudents from semesters 4 and 5
Description

• Ordinary differential equations

• First order systems, existence, uniqueness

• Applications : prey-predators, population dynamics, finance…

• Resolution of typical cases, linear systems

• Celestial mechanics

• Diffusion and heat equation, weak formulations

• Wave equation

• Elasticity

• Fluid mechanics

• Numerical approximations

Reading recommendations

Mandatory literature:

Course Lecture Notes (available on Moodle)

Additional literature/special activities:

• M. W. Hirsch, S. Smale : Differential equations, dynamical systems and linear algebra, Chapters 1-3

• M. Chipot : Element of nonlinear analysis, Chapter 1 + mentioned in the lecture notes

(FS23)

Lecturer

Prof. Dr Michel Chipot

Assistants

Researcher Antonella Nastasi

ECTS12
Repetition of Modulespring semester
Target AudienceStudents from semesters 4 and 5
Description

This course will cover the foundations of abstract algebra, focusing on the notions of group, ring and field. For each object we will present basic concept and some applications. In the case of groups: quotients, isomorphism theorems, the symmetric group, Sylow theorems. For rings: Ideals, polynomial rings, Principal Ideal Domains and notions of divisibility. For fields: field extensions, splitting fields. The narrative arc of the lecture will be organized around five “applicative goals”, each abutting one of the five blocks of the lecture. A tentative list includes: classification of regular polyhedra, applications in combinatorial game theory, the Chinese Reminder Theorem, Pick’s theorem, and the impossibility of angle trisection with ruler and compass.

 

Reading recommendations

Standard literature:

Lecture notes made available on moodle.

Additional literature/special activities:

To be determined and announced during the course

(FS23)

Lecturer

Dr Emanuele Delucchi

Assistants

Dr Andrea Adriani

ECTS10
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 6 and 7
Description

Description: This lectures gives an overview on theory and numerics for dynamical systems governed by ordinary differential equations.

Content: Picard-Lindelöff, Initial Value Problems, Existence, uniqueness of solutions, smoothness of solutions,lineare ODEs, stability, attractors, differential algebraic equations (DAEs), one-step methods, stability of numerical methods, stiff/non-stiff OFEs, Runge-Kutta methods, step-size control and global error, multi-step methods, collocation, multiple shooting, symplectic integrators, numerical methods for DAEs, parallel-in-tome methods (e.g. parareal).

Lecturer

ECTS10
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 6 and 7
Description

M13a Geometry

Projective geometry and the study of curves in the plane or surfaces in the space is a classical field in mathematics and an active area of research with a lot of beautiful results. The classification of quadrics and elliptic curves is a first step in the theory, followed by the study of intersections and singularities.

 

M13b Number theory

This is a very classical subject, starting with the field of rational numbers and its extensions, called number fields. A first highlight is Galois Theory, setting up a beautiful interaction between number fields and groups. Modern number theory is still one of the main research areas in mathematics. On the other hand, elementary number theory plays a fundamental role in cryptology and communication.

Lecturer

ECTS7
Repetition of Modulespring semester
Target AudienceStudents from semesters 6 and 7
Description

Description: This lecture gives an introduction to Differential Geometry

Content: Curves, manifolds, tangential space, vector fields, tangent bundles, symplectic forms. Total differential, Theorem of Stokes, Lie-groups.

Lecturer

ECTS6
Repetition of Modulespring semester
Target AudienceStudents from semesters 6 and 7
Description

M15a Topology

Description: This lecture gives an introduction to general topology or in Algebraic Topology. Topology is concerned with properties of geometrical objects that are preserved under continuous deformations. The abstract setting is a topological space and its behaviour under continuous maps. In the algebraic topology one can attach to a topological spaces algebraic objects, such as the homology groups or the fundamental group, which allows to distinguish topological spaces

Content: Topological Spaces, topologies, continuous mappings, separation axioms, filter, compactness, compactification, metrization

 

M15b Theory of Groups

The theory of groups and their representations appears in many fields in mathematics and also plays an important role in theoretical physics, e.g. in quantum mechanics and recently in quantum computing. Symmetries can be described by groups. Typical examples are the platonic solids which correspond to finite symmetry groups in space, and the crystallographic groups in space used for the classification of crystals.

 

M15c Combinatorics

Combinatorics is mainly concerned with enumerating and counting, and with structures on finite sets. It has many applications, in particular in statistics and computer science. Combinatorial problems arise in many areas of mathe-matics, e.g. in algebra, topology and in group theory. A classical subject is graph theory, going back to the 18th century.

 

Lecturer

ECTS7
Repetition of Modulespring semester
Target AudienceStudents from semesters 6 and 7
Description

Description: The course gives an introduction in Optimization and Machine Learning.

Content: Minima, stationary points, convex minimization, unconstrained minimization, KKT conditions, constraints (equality/inequality), Trust-region methods, SQP, BFGS, CG, linear Programing, Simplex, interior point, learning, supervised, unsupervised, re-inforcement learning, neuronal nets, convolutional networks, autoencoder, u-net, stochastic gradient method, backpropagation, accelerated gradient methods

Lecturer

ECTS14
Repetition of Moduleautumn semester
Target AudienceStudents from semesters 8 and 9
Description

Description: This lecture gives an introduction to the theory and numerics of partial differential equations (PDEs) and includes an integrated Lab.

Content: Definition of PDEs, clasification, boundary value problems, Sobolev spaces, elliptic problems, Poisson equation, heat equation, Green’s function, fundamental solution, weak formulation, solution, Lax-Milagram, Finite differences, finite elements, parabolic problems, stability, eigenfunctions, Fouriersolutions, method of Lines, Rothe’s method, advection, characteristics, hyperbolic equations, stability of finite diffrenece schemes, CFL-condition, conservation laws, finite Volume, error estimators, adaptivity, space-time formulations.

 

Integrated Lab

Content: Finite Differences, Finite Elements, mesh generation, non-linear finite elements, boundary conditions, a simple geometric multigrid, visualization.

Lecturer

ECTS6
Repetition of Modulespring semester
Target AudienceStudents from semesters 8 and 9
Description

The Module may content special topics from the fields of Algebraic Geometry, Geometry, Theory of Groups, Representation Theory of Groups, Number Theory, Topology or Combinatorics.

Lecturer

ECTS10
Repetition of Modulespring semester
Target AudienceStudents from semesters 8 and 9
Description

Students can choose from a catalogue of modules from the study courses of the other Faculties offered by FernUni Schweiz. The available modules from the Faculties of Economics, Psychology, Law and History are published every semester. The modules are given in the language of the study course.

Lecturer

ECTS10
Repetition of Modulespring and autumn semester
Target AudienceStudents from semesters 8 and 9
Description

This two-semester module consists of a seminar followed by a bachelor thesis. In the guided seminar, students will read, summarize, and present a mathematically advanced paper with the aim to consolidate the essential competence of mathematicians: “Comprehend – Transmit – Write up”. This is the basis for the bachelor thesis.

Lecturer

Do you have any questions?

Our Student Managers will be glad to help you in French, German or English.
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