Stud.IP Uni Oldenburg
University of Oldenburg
06.12.2021 13:05:39
mar366 - Current topics in modelling and data analysis (Complete module description)
Mar366 - Current topics in modelling and data analysis (Complete module description)
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Module label Current topics in modelling and data analysis
Module code mar366
Credit points 6.0 KP
Workload 180 h
(
Präsenzzeit: 56 Stunden, Selbststudium: 124 Stunden
)
Institute directory Institute for Chemistry and Biology of the Marine Environment
Applicability of the module
  • Master's Programme Marine Environmental Sciences (Master) > Mastermodule
Responsible persons
Blasius, Bernd (Module responsibility)
Ryabov, Alexey (Module counselling)
Prerequisites
Einführende Veranstaltung in mathematischer Modellierung
Skills to be acquired in this module

VL/Ü Machine learning in the environmental sciences

Die Studierenden erlernen neueste Methoden im Bereich der mathematischen Modellierung und Analyse von

Massendatensätzen (Big-Data) und deren

Anwendungsfelder. Sie sind in der Lage, die Analysen in der Sprache Matlab zu implementieren. Sie erlernen die Auseinandersetzung mit aktueller Literatur und die kritische Betrachtung neuester Methoden in Hinblick auf Datensicherheit und Nutzbarkeit im wissenschaftlichen Kontext.
Module contents

VL/Ü Machine learning in the environmental sciences
In this course the students will learn to think as a data scientist and ask questions about the data. First, we will learn how to work with tables and extract statistics on groups of data. Then, we will go to the basic approaches of machine learning: supervised learning (classification and regression trees, neural networks), unsupervised learning (cluster analysis, factor analysis), reducing system dimensions (PCA, MDA ect.), statistical modelling (regression, generalized linear models), and optimization of model parameters (simulated annealing, differential evolution). Finally, we will focus on typical workflow of the data processing. We will use Matlab to implement the algorithms.
Reader's advisory
Literatur wird in den Veranstaltungen bekannt gegeben.
Links
Languages of instruction German, English
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel / module level MM (Mastermodul / Master module)
Modulart / typ of module Wahlpflicht / Elective
Lehr-/Lernform / Teaching/Learning method VL Machine learning in the environmental sciences
(2 SWS, 3 KP)
S Machine learning in the environmental sciences
(2 SWS, 3 KP)
Vorkenntnisse / Previous knowledge
Course type Comment SWS Frequency Workload of compulsory attendance
Lecture
2 SuSe 28
Seminar
2 SuSe 28
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module

Präsentation oder Hausarbeit am Ende der Veranstaltungszeit nach Maßgabe der Dozentin oder des Dozenten.
KL