IS 723: Seminar Data-Science II

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.

Learning outcomes
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

Necessary prerequisites

Recommended prerequisites
lectures offered by the chair

Forms of teaching and learningContact hoursIndependent study time
Seminar2 SWS15 SWS
ECTS credits6
Graded yes
Form of assessmentWritten report (60%) with oral presentation (40%)
Restricted admissionyes
Further informationWebsite of the chair
Performing lecturer
Prof. Dr. Markus Strohmaier
Prof. Dr. Markus Strohmaier, Marlene Lutz
Frequency of offeringSpring semester & fall semester
Duration of module 1 semester
Range of applicationM.Sc. MMM, M.Sc. Bus. Edu., MMDS
Preliminary course work
Program-specific Competency GoalsCG 4
LiteratureDepending on the assigned topics.
Course outlineThe 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.