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[ 986CAINCI4K19 ] KS CI4: Data-driven management
Versionsauswahl
Es ist eine neuere Version 2022W dieser LV im Curriculum Master's programme Leading Innovative Organizations 2022W vorhanden.
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year Business Administration Sophie Parragh 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites KS BC1: Induction-team development UND KS BC2: Foundations of management UND KS BC3: Foundational readings and academic writing
Original study plan Master's programme Leading Innovative Organizations 2021W
Objectives
  • Students are able to set up models from data to provide decision support
  • They understand the basic data mining techniques
  • They know how to interpret the obtained results
Subject
  • Data analytic thinking
  • Data understanding und visualization
  • Predictive modeling (classification)
  • Model evaluation
  • Software tools
  • Applications
Criteria for evaluation Attendance and participation (20%); Pre-readings (20%); Post-module assignment (60%)
Methods Lecture, discussion
Language English
Study material Provost, F., and Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc." Dimitris Bertsimas, Allison O’Hair and William Pulleyblank, The Analytics Edge by, Dynamic Ideas LLC, 2016 Hillier, Lieberman. Introduction to Operations Research. In the current edition. Pointers to additional reading material will be provided during the course.
Changing subject? No
On-site course
Maximum number of participants 40
Assignment procedure Direct assignment