GEOMAR  Career & Campus  Campus  Studying  MSc: Biological Oceanography  Summer semester 2024 - Examination schedule / Course List / Time tables

Summer semester 2024

General remarks

General lecture period summer semester 2024: 15.04.2024 to 12.07.2024 (with winter semester 2023/2024, 2nd exam period: 02.04. - 13.04.2024 (link CAU) - In accordance with the CAU's examination procedure regulations, there are no courses in bachelor's and master's degree programs during the examination periods (few exceptions for first semester students)).

More information at M. Sc. Biological Oceanography - information for students on OLAT.

Exam dates summer semester 2024: here (OLAT)

There is no general registration for courses - only for the exams at the end of the semester during registration phases (s.b.).

Notes on how to use the online tool can be found here:

If you have questions about the examination administration procedures in general (registration periods, examination periods, etc.) you may find answers in the Examination procedures section. If you are still unclear about anything you can contact the relevant Examination Office at any time.

Complete examination schedule SS 2024 (link to CAU).

Examinations:

Typical examination procedure:     

  1. Examination registration: You register for the examinations that you would like to take in the next examination period or that are assigned to the next examination period (s.b. Examination Organisation Online (CAU)). In case of registration problems contact the Examination Office Biology.

    During the registration period for the 1st examination period please register for all the written or oral examinations you would like to take in the 1st examination period (or around and assigned to the 1st examination period), but also for the examinations that you have already taken or started (e.g. seminar papers) during the lecture period (including before the registration period), as well as for examinations (e.g. assignments) that are to be taken during the lecture-free period.

    Note: For examinations taken before the registration period, examination attendance is considered as binding registration. You must also register for these examinations during the registration period, however, so that your academic achievements can be recorded in the system at a later stage.

  2. Checking admission: Two days before the start of the examination period, you check whether you have been granted admission to the examinations you have registered for.
  3. Examination attendance: You take the examinations during the examination period.
  4. Checking results: You check the results entered by the examiners.

Examination Organisation Online (CAU)

Access to the online tool in the CAU-Portal: http://www.uni-kiel.de/hisinone

The online tool has the following functions:

  • Registering for examinations / Cancelling registrations
  • Information on registered examinations (checking admissions. Information on examination dates, times and rooms)
  • Information on examination results
     

Notes on how to use the online tool can be found here:

You need your stu-ID to use the Studierenden-Online-Funktion online tool. Detailed information on the stu-ID and stu-e-mail address can be found at the Computing Centre StudiNet.

If you have questions about the examination administration procedures in general (registration periods, examination periods, etc.) you may find answers in the Examination procedures section. If you are still unclear about anything you can contact the Examination Office Biology at any time.

Registration period first exam phase summer semester: 03.06.2024 - 30.06.2024

First exam period summer semester: 15.07.2024 - 27.07.2024

Registration period second exam period summer semester: 26.08.2024 - 22.09.2024

Second exam period winter semester: 07.10.2024 - 19.10.2024 

Complete schedule see CAU website and here (link to CAU).

Keep in mind - it's your responsibility not to miss any fixed dates and/or deadlines.

Practical courses, practical exercises and some seminars have compulsory attendance (FPO).

Make sure that you sign the attendance list every course day!

Framework of courses:

  1. All of the five first semester modules are compulsory.
  2. Passed core modules of the first semester (MNF-bioc-101 and MNF-bioc-102) are important for the understanding for the advanced modules of the second semester in summer (e.g. MNF-bioc-201 and MNF-bioc-202).
  3. Passed exams of ALL compulsory modules of first and second semester are the  indispensable prerequisite for the exam of the core module of third semester in winter (MNF-bioc-301).
  4. A short presentation of your planned master's thesis ("proposal day") and a passed exam at the end of MNF-bioc-301 is the prerequisite to register your thesis (MNF-bioc-401) at the examination office.

For details concerning exams, prerequisites etc. look at the exam regulations in Biological Oceanography (p. 10-13).

Forms concerning exam withdrawal for good cause, medical certificate etc. (forms).

General regulations concerning examinations can be found here.

Considerations concerning using first or second exam phase (CAU).

Exams are generally scheduled only for the semester where the modules are taught.

  • There are no exams for winter semester modules MNF-bioc-1xx and MNF-bioc-3xx in summer semester.
  • There are no exams for summer semester modules MNF-bioc-2xx in winter semester.

Examination Schedule (lecturers and students tasks (link to CAU)

 

Timetables and course lists

General: Courses (lectures, seminars, practicals etc.) summer semester 2024

MSc. Biological Oceanography - second semester - lecture plan summer semester 2024 (click on "Stundenplan" for a complete time table).  All seven different possible practical parts in three blocks of MNF-bioc-202 are shown which looks heavily loaded - but you have to choose only two resp. three non overlapping parts.

Details: More detailed information concerning single courses and modules can be found on OLAT in general, resp. M. Sc. Biological Oceanography - information for students or via our module list, with links to the resp. module information on OLAT.

As you can take many optional modules outside of our curriculum (CAU-wide choices) these are not included in the example lists and timetables.

Block courses in summer 2024: 

  • MNF-bioc-264 (S. Garthe, Büsum): September/October 2024
  • MNF-bioc-271 (B. Schneider, Kiel): 21.05.2024 - 24.05.2024
  • MNF-bioc-280 (K. Heubel, FTZ): 26.08.2024 - 06.09.2024 at FTZ Büsum.
  • MNF-bioc-301 (F. Mittermayer, ALKOR cruise MNF-bioc-301): 18.08.2024 - 30.08.2024
  • MNF-bioc-368 (F. Weinberger, Aaland-Island (Finland) - Marine station Husö): 07.09.2024 - 22.09.2024

  • For optional modules within Biological Oceanography look at the module list.
  • Generally: for imported courses (e.g. Introduction to Physical Oceanography) and and courses outside of M. Sc. Biological Oceanography please always contact the person in charge of the module you are attending and the corresponding exam office.
  • For a selection of courses outside of our curriculum look here (optional courses outside of Biological Oceanography).

Summer semester 2024

UnivIS
Informationssystem der Universität Kiel © Config eG 
Semester: SS 2024 

Finanzmathematik und Stochastische Integration / Mathematical Finance and Stochastic Integration (V:FinMathStochInt) (060203)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Vorlesung, 4 SWS
Praesenzveranstaltung, Unterrichtssprache Englisch
Zeit und Ort: Di 8:15 - 9:45, HHP6 - R.EG.001; Fr 10:15 - 11:45, HHP6 - R.EG.001
vom 16.4.2024 bis zum 12.7.2024

Studienfächer / Studienrichtungen
PFL FinMath-MSc 2

Voraussetzungen / Organisatorisches
Basic knowledge of measure-theoretic probability. Knowledge of stochastic processes is not required, but helpful.
Modultitel:
Mathematical Finance
Modultitel:
Finanzmathematik und stochastische Integration
Modulhandbuch:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Module alphabetisch:
http://www.math.uni-kiel.de/go/module
Modulcode: math-stifi:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/math-stifi.pdf
Zielgruppe:
1-Fach-Master Mathematik (Wahlbereich)
1-Fach-Master-Finanzmathematik (Pflicht)
Master Mathematics, Master Mathematical Finance
Link auf Internetseite:
https://lms.uni-kiel.de/url/RepositoryEntry/5434671277

Inhalt
When modeling random processes in time, one often encounters stochastic integrals - integrals whose integrand and integrator are stochastic processes. The resulting theory is rich and interesting from a mathematical point of view, but also plays an important role in many applications, for example in modern financial mathematics, but also in natural sciences and engineering. Stochastic calculus also plays a role in modern machine learning techniques such as stable diffusion.
The course is split in two parts:
1. Stochastic Calculus
2. Application to continuous time models for financial markets
It is possible to take only the first part of the course and complete it with a module examination.
Even if stochastic integrals appear again and again in a natural way, the stringent definition is not very easy and requires an expansion of the known notions of integrals. In this course we will also introduce the stochastic integral for jump processes, but then always work with continuous semimartingales to avoid technical problems. Based on this definition, we develop a calculus, the Itô calculus, which enables easy handling of stochastic integrals. At the end of the first part of the course, we will deal with internal and external mathematical applications of the previously developed theory.
The second part of the course deals with financial markets from a mathematical point of view. In particular, the analysis and evaluation of financial derivatives in realistic models requires knowledge of stochastic integration in order to be able to formulate the basic terms at all. On this basis, however, a critical understanding of the theory and practice of the financial markets can be developed. In doing so, we develop an exciting interplay between very practical questions and deep-seated mathematics.
We are particularly concerned with the (arbitrage-free) valuation of options. As an application of the theory, we will examine financial market models of the Black-Scholes type in more detail, but not limit ourselves to this model, but also consider models with jumps and stochastic volatility models.

Empfohlene Literatur
  • A. Irle. „Finanzmathematik“. Teubner.

Weitere Literatur wird ggf. in den Lehrveranstaltungen bekanntgegeben.

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15

Zugeordnete Lehrveranstaltungen
UE: Übung zu Finanzmathematik und Stochastische Integration
Dozent/in: Prof. Dr. Sören Christensen


Mathematics of Reinforcement Learning (MathReinf) (060329)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Vorlesung, 2 SWS
Praesenzveranstaltung, Unterrichtssprache Englisch
Zeit und Ort: Mi 12:15 - 13:45, HHP6 - R.EG.001; Fr 8:15 - 9:45, HHP6 - R.EG.001
vom 17.4.2024 bis zum 31.5.2024

Voraussetzungen / Organisatorisches
In addition to the basics of stochastics, no special prior knowledge is required.
Modulhandbuch:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Modulcode: mathAKdS5-01a:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/mathAKdS5-01a.pdf
Modulcode: mathAKdF-01a:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/mathAKdF-01a,.pdf
Modulcode: mathAKdW-01a:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/mathAKdW-01a.pdf
Modulcode: mathAKaNuF-01a, 5 LP:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/mathAKaNuF-01a.pdf
Zielgruppe:
1-Fach-Master Mathematik
2-Fach-Master Mathematik
1-Fach Master Finanzmathematik
Link auf Internetseite:
https://lms.uni-kiel.de/url/RepositoryEntry/5434671278

Inhalt
Reinforcement learning refers to a set of machine learning methods in which future decisions are made based on past successes and failures. It is assumed that the decision maker does not know (exactly) the underlying environment. Such methods play a central role in many modern applications, for example in the training of Google's "AlphaZero". The classic example of the "bandit" problem illustrates the basic issues: You are in a casino and want to choose one of the many slot machines ("one-armed bandits") in each round. However, you do not know the payoff distribution of the machines. In the beginning, you will probably just try the machines ("exploration") and then, after some learning, choose the (apparently) best ones ("exploitation"). However, the problem is that if you use one machine a lot, you may not learn anything about the others, and you may not even find the best machine ("Exploration-Exploitation Dilemma"). So what should you do? In this course, we will introduce basic mathematical ideas and notations, and also examine algorithms for solving them. We consider mathematical methods to describe important concepts in reinforcement learning, such as bandit problems, Markov decision processes, and deep learning.

Empfohlene Literatur
Lecture notes and additional literature will be provided

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15

Zugeordnete Lehrveranstaltungen
UE: Übung zu Mathematics of Reinforcement Learning (060063)
Dozent/in: Prof. Dr. Sören Christensen
Zeit und Ort: n.V.


Oberseminar Stochastik und Finanzmathematik (OS:StochFinanzmath) (060427)

Dozentinnen/Dozenten
Prof. Dr. Mathias Vetter, Prof. Dr. Sören Christensen

Angaben
Oberseminar, 2 SWS
Praesenzveranstaltung, Unterrichtssprache Englisch
Zeit und Ort: Do 10:15 - 11:45, HHP6 - R.EG.002; Einzeltermin am 21.6.2024 15:45 - 18:30, HHP6 - R.EG.025
vom 18.4.2024 bis zum 11.7.2024

Voraussetzungen / Organisatorisches
Modulhandbuch:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Module alphabetisch:
http://www.math.uni-kiel.de/go/module
Modulcode: math-osem-fima.pdf
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/math-osem_fima.pdf
Zielgruppe:
1-Fach Mathematik
1-Fach Finanzmathematik
Link zu OLAT:
https://lms.uni-kiel.de/auth/RepositoryEntry/5284986978/CourseNode/107103678409109

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15


Seminar Stochastik (S:Stoch) (060575)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Seminar, 2 SWS
Praesenzveranstaltung
Zeit und Ort: Di 12:15 - 13:45, HHP6 - R.EG.001; Mi 14:15 - 15:45, HHP6 - R.EG.004 (außer Mi 19.6.2024); Einzeltermin am 19.6.2024 14:15 - 15:45, LMS4 - R.325
vom 16.4.2024 bis zum 10.7.2024
Bemerkung zu Zeit und Ort: Der Termin am Mittwoch findet nur bei ausreichender Teilnehmerzahl statt

Studienfächer / Studienrichtungen
WPFL Math-MEd ab 7
WPFL Math-BScBA 4

Voraussetzungen / Organisatorisches
Modultitel:
Seminar Stochastik
Modulhandbuch:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Module alphabetisch:
http://www.math.uni-kiel.de/go/module
Modulcode: math-sem-stoch.1
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/math-sem_stoch.1.pdf
Zielgruppe:
1-Fach-Bachelor Mathematik (Wahlbereich)
2-Fächer-Master Mathematik (Wahlbereich)
Link zu OLAT:
https://lms.uni-kiel.de/url/RepositoryEntry/5434671326
Das Seminar kann auch von Lehramtsstudierenden belegt werden. Allerdings sind die Themen nicht direkt dafür ausgelegt. Wir empfehlen für Lehramtsstudierende daher den Besuch des Lehramtsseminars Stochastik.

Inhalt
Aufarbeitung eines klassischen Problems der Wahrscheinlichkeitstheorie, nach Wahl der Studierenden

Empfohlene Literatur
wird passend zum Seminarthema bereitgestellt.

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15


Seminar Stochastik und Finanzmathematik (MSc) (S:SemStochFinMSc) (060566)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Seminar, 2 SWS
Praesenzveranstaltung
Zeit und Ort: Di 12:15 - 13:45, HHP6 - R.EG.001; Mi 14:15 - 15:45, HHP6 - R.EG.004 (außer Mi 19.6.2024); Einzeltermine am 5.6.2024, 12.6.2024 8:15 - 9:45, HHP6 - R.EG.001; 19.6.2024 14:15 - 15:45, LMS4 - R.325
vom 16.4.2024 bis zum 9.7.2024
Bemerkung zu Zeit und Ort: Der Termin am Mittwoch findet nur bei ausreichender Teilnehmerzahl statt

Voraussetzungen / Organisatorisches
Stochastik I
Dieses Seminar richtet sich an alle Studierenden mit Interesse an einem Seminar in den Bereichen Stochastik oder Finanzmathematik. Die einzelnen Themen werden auf die individuellen Vorkenntnisse abgestimmt.
Modulhandbuch:
http://www.math.uni-kiel.de/go/module
Neue Version des Modulhandbuches mit Studienverlaufsplänen:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Modulcode: math-sem-fma-m.pdf
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/math-sem_fma_m.pdf
Zielgruppe:
1-Fach-Master Mathematik
1-Fach Master Finanzmathematik
Link auf OLAT-Seite:
https://lms.uni-kiel.de/url/RepositoryEntry/5434671326

Inhalt
Dieses Seminar richtet sich an alle 1-Fach-BSc./MSc.-Stud. mit Interesse an einem Seminar in den Bereichen Stochastik und Finanzmathematik. Die einzelnen Theman werden auf die individuellen Vorkenntnisse abgestimmt. Als Oberthema ist stochastistische Steuerungstheorie vorgesehen.

Empfohlene Literatur
wird in der Vorbesprechung bekannt gegeben

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 8


Stochastische Integration / Stochastic Integration (V:StochInt) (060856)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Vorlesung, 2 SWS
Praesenzveranstaltung, Unterrichtssprache Englisch, *Diese Vorlesungszeiten gelten nur für die erste Semesterhälfte.**Es finden mündliche Prüfungen in Präsenz statt!*
Zeit und Ort: Di 8:15 - 9:45, HHP6 - R.EG.001; Fr 10:15 - 11:45, HHP6 - R.EG.001
vom 16.4.2024 bis zum 31.5.2024
Bemerkung zu Zeit und Ort: Diese Veranstaltung findet in der ersten Semesterhälfte statt

Studienfächer / Studienrichtungen
PFL FinMath-MSc 2

Voraussetzungen / Organisatorisches
Stochastik I
Modultitel:
Stochastische Integration/Stochastic Integration
Modulhandbuch:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module
Module alphabetisch:
http://www.math.uni-kiel.de/go/module
Modulcode: mathStoInt-01a:
https://www.math.uni-kiel.de/de/studium_und_lehre/studienverlauf-module/module/mathStoInt-01a.pdf
Zielgruppe:
1-Fach-Master Mathematik (Wahlbereich)
zu dieser Vorlesung werden die Übungen Finanzmathematik und Stochastische Integration / Mathematical Finance and Stochastic Integration mitbenutzt
Link zu OLAT:
https://lms.uni-kiel.de/url/RepositoryEntry/5434671277

Inhalt
When modeling random processes in time, one often encounters stochastic integrals - integrals whose integrand and integrator are stochastic processes. The resulting theory is rich and interesting from a mathematical point of view, but also plays an important role in many applications, for example in modern financial mathematics, but also in natural sciences and engineering. Stochastic calculus also plays a role in modern machine learning techniques such as stable diffusion. This course will be continued in the second half of the semester by the course "Mathematical Finance and Stochastic Integration". See that univis entry for more information.

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 18


Übung zu Finanzmathematik und Stochastische Integration (Ü:FinmathStochInt)

Verantwortliche/Verantwortlicher
Prof. Dr. Sören Christensen

Angaben
Übung, 2 SWS

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15

Zugeordnet zu: Finanzmathematik und Stochastische Integration / Mathematical Finance and Stochastic Integration (060203)

Kurse
      060465
Do  14:15 - 15:45  HHP6 - R.EG.003
Kurs vom 18.4.2024 bis zum 11.7.2024, erwartete Teilnehmer: 15
Sören Christensen


Übung zu Mathematics of Reinforcement Learning (ÜMathReinf) (060063)

Dozent/in
Prof. Dr. Sören Christensen

Angaben
Übung, 1 SWS
Praesenzveranstaltung, Unterrichtssprache Englisch
Zeit und Ort: n.V.

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 15

Zugeordnet zu: Mathematics of Reinforcement Learning (060329)

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