Syllabus

Title
1391 Data Mining and Decision Support Systems
Instructors
Prof. Dr. Christian Fikar, MSc.
Contact details
Type
PI
Weekly hours
3
Language of instruction
Englisch
Registration
08/31/18 to 10/28/18
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Wednesday 11/07/18 09:00 AM - 12:30 PM LC.-1.038
Wednesday 11/14/18 08:30 AM - 01:00 PM LC.-1.038
Wednesday 11/21/18 09:00 AM - 01:30 PM LC.-1.038
Wednesday 11/28/18 08:00 AM - 12:30 PM LC.-1.038
Wednesday 12/05/18 09:00 AM - 01:30 PM LC.-1.038
Wednesday 12/12/18 08:00 AM - 12:30 PM LC.-1.038
Wednesday 01/09/19 09:00 AM - 01:30 PM LC.-1.038
Wednesday 01/16/19 09:00 AM - 11:30 AM D3.0.225
Contents

The course provides an introduction to data mining and model-driven decision support systems. Concepts, methods and examples are provide, with a focus on acquiring hands-on experience with widely used methods, libraries and software systems.

Learning outcomes

After completing the course, students will know how to handle a number of basic data mining methods and how to provide computer-aided decision support. 

Attendance requirements

Continuous assessment courses (PI) requiring attendance according to the rule set of the Master’s program.

Teaching/learning method(s)

Each session combines classic lectures with interactive examples, which provides students with an immediate hands-on experience of various methods. Students are required to prepare reading material for each lecture and complete homework exercises after each session.  Alongside the course, students will work in groups on a data mining project of their choice, for which separate coaching sessions will be offered and which will be presented to class for peer discussion at the end of the course. 

Assessment
  • Exercises: 30%
  • Group Project: 30%
  • Final exam: 40%
Prerequisites for participation and waiting lists
Basic programming skills, statistics and linear algebra.
Readings
1 Author: Ledolter, Johannes
Title:

Data Mining and Business Analytics with R


Publisher: Wiley
Year: 2013
Content relevant for class examination: No
Content relevant for diploma examination: No
Recommendation: Reference literature
Type: Book
Availability of lecturer(s)

christian.fikar@wu.ac.at

Last edited: 2018-11-22



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