Foundations of Data Mining
Grundlagen des Data Mining
6 LPWiSeEN
Voraussetzungen
Zwingend, im Wortlaut
• No successful participation in module 12351 Grundlagen des Data Mining.
Empfohlen, im Wortlaut
The module cannot be successfully completed without knowledge of the content of • 11112 Mathematik IT-1 (Diskrete Mathematik) • 11113 Mathematik IT-2 (Lineare Algebra)
Inhalte
• Foundation of statistics • Clustering (partition-based, density-based, hierarchical, ...) • Classification (decision trees, support vector machines, deep learning on convolution neural networks, ...) • Association rules (frequent itemsets) • further data mining approaches Acquired knowledge will be applied within a project.
Lernziele
Acquaintance with the statistical and learning-theoretical foundations of knowledge extraction from large data sets; knowledge of specific notions and of mathematical background in order to understand current publications and software concerning the field; ability of transfer to concrete problems; knowledge of algorithms and their usage.
Prüfungsleistung
Prerequisite: • Successful completion of practical training tasks and exercises tasks Final module examination: • Written examination, 90 min. OR • Oral examination, 30-45 min. (with small number of participants) In the first lecture it will be annunced, if the examination will offered in written or oral form.
Literatur (3)
- James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert: An Introduction to Statistical Learning with Applications in R. Springer, New York 2013.
- Aloaydin, Ethem: Machine Learning. The MIT Press, Massachusetts Institute of Technology, 2004.
- Mitchell, Tom M.: Machine Learning. McGraw-Hill, 1997.
Bemerkungen
• Study programme Informatik B.Sc.: Compulsory elective module in complex „Grundlagen der Informatik” (level 300) • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Knowledge Acquisition, Representation, and Processing” • Study programme Cyber Security M.Sc.: Compulsory elective module in complex „Computer Science” • Study programme Mathematik B.Sc.: Compulsory elective module in complex „Anwendungen”, field „Informatik” • Study programme Wirtschaftsmathematik B.Sc.: Compulsory elective module in complex „Anwendungen”, field „Informatik” • Study programme Mathematical Data Science M.Sc.: Compulsory elective module in complex „Fundamentals of Data Science” If there is no need that the module is taught in English, alternatively the german version 12351 „Grundlagen des Data Mining” may be offered instead. Module 11881 „Foundations of Data Mining” and 12351 „Grundlagen des Data Mining” can not be combined.
Quelle: Modulbeschreibung der BTU · abgerufen 28.09.2026Original