Modulcode:	infSemDaSci-01a
Englische Bezeichnung:	Master Seminar - Data Science
Modulverantwortliche(r):	Prof. Dr. Matthias Renz
Turnus:	jedes Semester (SS20 SS21 WS21/22 SS22 SS23 SS24)
Präsenzzeiten:	2S
ECTS:	5
Workload:	30 h seminar, 120 h self studies
Dauer:	ein Semester
Modulkategorien:	MSc-Inf-Sem (MSc Inf (21)) 2F-MA-Inf-Sem (2F-MA Inf (21)) MSc-WInf-Sem (MSc WInf (21)) Sem (MSc Inf (15)) Sem (MSc WInf (15))
Lehrsprache:	Englisch
Voraussetzungen:

Kurzfassung:

This seminar discusses current topics and new developments in the field of data science with special focus on data mining, machine learning and predictive analytics among others. The students are expected to choose from a pre-selection of topics. The material of study covering conference papers, journal articles and book chapters will be provided. Students tasks include a written assignment and a talk of 20-30 mins together with a short discussion besides active participation in the seminar.

Lernziele:

The students can

• read and understand scientific texts
• preparen and present a scientific talk over 30 mins
• write a summary of the given topic and present acquired knowledge
• understand research literature, produce a corresponding written text and give a talk that exceeds the level of a Bachelor seminar

Lehrinhalte:

State-of-the-art and latest methods and algorithms in the folowing fields:

• data science
• data mining
• knowledge discovery
• large-scale data analytics
• big data.

Weitere Voraussetzungen:

Basic knowledge on data mining is recommended.

Prüfungsleistung:

• Scientific presentation and discussion
• Written summary

Lehr- und Lernmethoden:

The literature research and the preparation of the talk and the written summary should mostly be done independently.

Verwendbarkeit:

Literatur:

Will be handed out in the beginning of the seminar.

Verweise:

Kommentar:

For asking for available seats and other related questions, please write an e-mail to ag-renz-lehre@lists.uni-kiel.de