Lerninhalte
The achievement of the learning goals is pursued by practicing on the basis of personally assigned in-depth scientific topics as well as by actively participating in the presentation dates. The organizer will choose subject areas within the field of Data-Science and provide scientific papers to students to work through.
Lern- und Qualifikationsziele
Skills: On the basis of suitable literature, in particular original scientific articles, students independently familiarize themselves with a topic in data-science, classify and narrow down the topic appropriately and develop a critical evaluation. Students work out concepts, procedures and results of a given topic clearly and with appropriate formalisms in a timely manner and to a defined extent in depth in writing; Evidence of independent development by presenting self-selected examples. Descriptive oral presentation of an in-depth data science topic using suitable media and examples in a given format
Notwendige Voraussetzungen
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Inhaltliche Voraussetzungen
lectures offered by the chair
Lehre | Selbststudium | |
---|---|---|
Seminar | 2 SWS | 15 SWS |
ECTS | 6 |
Sprache | Englisch |
Prüfungsform und -umfang | Written report (60%) with oral presentation (40%) |
Zulassungsbeschränkt | Ja |
Informationen zur Anmeldung | Website of the chair |
Geprüft durch Durchführende Lehrkraft | ![]() | Prof. Dr. Markus Strohmaier Prof. Dr. Markus Strohmaier, Marlene Lutz |
Angebotsturnus | Frühlings-/ |
Dauer des Moduls | 1 Semester |
Verwendbarkeit | M.Sc. MMM, M.Sc. WiPäd |
Vorleistungen | – |
Programmspezifische Kompetenzziele | CG 4 |
Benotung | Ja |
Literatur | Depending on the assigned topics. |
Gliederung | The seminar will kick off with an assignment of subtopics in data-science, afterwards students will work through papers and related literature. A written report is produced and the work is presented and discussed in joint meetings. |