Data Mining

Faculty

Faculty of Business Management and Social Sciences

Version

Version 1 of 31.01.2025.

Module identifier

22B0332

Module level

Bachelor

Language of instruction

German

ECTS credit points and grading

5.0

Module frequency

only winterterm

Duration

1 semester

 

 

Overall workload

The total workload for the module is 150 hours (see also "ECTS credit points and grading").

Teaching and learning methods
Lecturer based learning
Hours of workloadType of teachingMedia implementationConcretization
30LecturePresence-
30PracticePresence-
Lecturer independent learning
Hours of workloadType of teachingMedia implementationConcretization
40Preparation/follow-up for course work-
30seminar paper-
20Exam preparation-
Graded examination
  • Homework / Assignment or
  • Portfolio exam or
  • Written electronical examination
Literature

Kamber; Han: Data Mining Concepts and Techniques, Morgan Kaufmann. Ester; Sander: Knowledge Discovery in Databases. Techniken und Anwendungen. Springer, Berlin 2000. Wickham, H.; Grolemund, G.: R for Data Science, Verlag O'Reilly, 2016 Torgo, L.: Data Mining with R, Verlag CRC Press, 2011 Lantz, B.: Machine Learning with R. 3. Edition, Verlag Packt> Weitere Literatur wird w?hrend der Veranstaltung angegeben.

Applicability in study programs

  • Business Information Systems - WiSo
    • Business Information Systems B.Sc. (01.09.2024) WiSo

    Person responsible for the module
    • Dallm?ller, Klaus
    Teachers
    • Dallm?ller, Klaus