Inhalt

[ 926BUSIDAM13 ] Module Data Mining

Versionsauswahl
Es ist eine neuere Version 2023W dieses Fachs/Moduls im Curriculum Master's programme Economic and Business Analytics 2023W vorhanden.
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Workload Mode of examination Education level Study areas Responsible person Coordinating university
6 ECTS Accumulative module examination M1 - Master's programme 1. year Business Informatics Michael Schrefl Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Business Informatics 2016W
Objectives Students are enabled to apply data mining methods and techniques to recognize patterns that reveal potentially unknown knowledge from integrated and cleaned organizational data bases. They know the phases of the data mining process, important domains and typical problems as well as current developments of data and Web mining, and are familiar with common data mining tools.
Subject Data mining process (KDD - Knowledge Discovery in Data); Data mining techniques: Clustering, Classification, Association rules; Data mining applications; Data mining tools; current developments; Case studies and practical scenarios, with a particular focus on web mining.
Further information Lecture and exercise can be combined to one course.
Subordinated subjects, modules and lectures