Modul


Allgemeine Informationen
Thesis
Thesis
MADS-T
Prof. Dr. Doerfel, Stephan (stephan.doerfel@haw-kiel.de)
Prof. Dr. Prange, Michael (michael.prange@haw-kiel.de)
Prof. Dr. Schwörer, Tillmann (tillmann.schwoerer@haw-kiel.de)
Prof. Dr. Doerfel, Stephan (stephan.doerfel@haw-kiel.de)
Prof. Dr. Prange, Michael (michael.prange@haw-kiel.de)
Prof. Dr. Schwörer, Tillmann (tillmann.schwoerer@haw-kiel.de)
Sommersemester 2024
1 Semester
In der Regel jedes Semester
Englisch
Studiengänge und Art des Moduls (gemäß Prüfungsordnung)
Studiengang Vertiefungsrichtung Schwerpunkt Modulart Fachsemester
M.Sc. - DS - Data Science Pflichtmodul

Kompetenzen / Lernergebnisse
Kompetenzbereiche: Wissen und Verstehen; Einsatz, Anwendung und Erzeugung von Wissen; Kommunikation und Kooperation; Wissenschaftliches Selbstverständnis/Professionalität.
Students
- are able to translate a practically or academically relevant data science problem into a theoretical research framework.
- can familiarize themselves with the relevant research publications and possibly identify research gaps and are capable to provide a theoretical overview summarizing the current state of research.
- can identify and select the appropriate research methodology to address the chosen research question.
Students
- are able to professionally prepare and execute a project own their own, either in an academic or corporate environment, delivering the results in time.
- are able to apply their competencies to analyze, structure and solve complex problems, building on state of the art technologies and methods.
- are able to prepare a research paper in compliance with norms for academic and scholarly expression and for publication in the public domain.
Students
- are capable to organize themselves individually in an effective manner to set the right priorities and manage their resources to successfully meet the requested academic requirements.
- are capable to present and defend their research project in front of a qualified academic audience.
- respond to criticism in an open self-reflective constructive manner.
Students
- can apply the academic rules of conduct expected by a researcher to achieve an objective, valid, reliable and ethically justifiable research outcome.
- can conduct themselves in a professional and respectful manner in particular with respect to the time made available by their supervisor by being well prepared for meetings and request for appointments in writing with the questions and or issues to be addressed clearly laid out in advance.
Angaben zum Inhalt
In the Master Thesis, the candidate should demonstrate that he or she is able to independently carry out a research project in any of the disciplines offered by the Data Science Master program such as Machine Learning, Deep Learning, Data Management, Cloud Computing, Big Data Technologies, Data Visualization, Natural Language Processing, or some related field. The Master Thesis can be either an academic research project or a practical data science project in a corporate environment. The topic of the thesis is determined in consultation with the candidate and the supervising lecturer.
Lehrformen der Lehrveranstaltungen
Lehrform SWS
Keine Präsenzzeit 0
Arbeitsaufwand
0 SWS
25,0 Leistungspunkte
0 Stunden
750 Stunden
Modulprüfung
For admission to the final thesis, all examinations of the compulsory modules must have been passed.
Prüfungsform Dauer Gewichtung wird angerechnet gem. § 11 Absatz 2 PVO Benotet Anmerkung
Abschlussarbeit (Thesis) 100 %