Modulcode:	Inf-MP-AOS
Englische Bezeichnung:	Master project - Algorithmic Optimal Control / Climate Simulation
Modulverantwortliche(r):	Prof. Dr. Thomas Slawig
Turnus:	jedes Semester (WS16/17 SS17 WS17/18 SS18 WS18/19 SS19 WS19/20 SS20 WS20/21 SS21 WS21/22 SS22 SS24)
Präsenzzeiten:	4PÜ
ECTS:	10
Workload:	60 h group excercise, 240 h self-study and self-organized group work
Dauer:	ein Semester
Modulkategorien:	MSc-Inf-Proj (MSc Inf (21)) 2F-MSc-Proj (2F-MA Inf (21)) Proj (MSc Inf (15))
Lehrsprache:	Englisch
Voraussetzungen:

Kurzfassung:

Project on methods of modeling, simulation, optimization and computer science based on examples usually from climate and environmental research.

Lernziele:

The students are able to understand and work on scientific problems in climate research, with special focus on simulation, optimization and machine learning. They can run simulations and write or modify existing simulation, optimization or machine learning software. They are able to summarize, document and present their results and to actively participate in teamwork.

Lehrinhalte:

Mostly models and topics from the field of climate or environmental research are dealt with. Application problems motivated by current research are investigated. Topics can be modeling, discretization and effective simulation, software design, parallelization, optimization and machine learning or combinations of these.

Weitere Voraussetzungen:

Programming skills, knowledge of optimization and/or machine learning methods and software is an advantage. Willingness to learn to work with existing software.

Prüfungsleistung:

Oral module examination in the form of a presentation of results in a lecture, project elaboration or software documentation, if applicable.

Lehr- und Lernmethoden:

Individual work, group work, presentation

Verwendbarkeit:

Literatur:

Will be given in the project about individual topics.

Verweise:

Kommentar:

More detailed information on the topics in a respective semester will be given in UnivIS.