Studienhandbuch | KS CI4: Data-driven management

Inhalt

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 BC2: Induction: Team development UND KS BC1: Foundations of management UND KS BC3: Foundations of management science
Original study plan	Master's programme Leading Innovative Organizations 2022W
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