Data Mining (FSS 2020)

The course provides an introduction to advanced data analysis techniques as a basis for analyzing business data and providing input for decision support systems. The course will cover the following topics:

  • The Data Mining Process
  • Data Representation and Preprocessing
  • Clustering
  • Classification
  • Regression
  • Association Analysis
  • Text Mining

The course consists of a lecture together with accompanying practical exercises as well as student team projects.  In the exercises the participants will gather initial expertise in applying state of the art data mining tools on realistic data sets. The team projects take place in the last third of the term. Within the projects, students realize more sophisticated data mining projects of personal choice and report about the results of their projects in the form of a written report as well as an oral presentation.

The webpage about the HWS 2019 edition of this course is found in the lecture archive.

Exam Review

The exam review for the exam of FSS2020 will take place on Friday, 9 October 2020, from 11:00–12:00, building B6, 26 room C1.01 (use the blue door and go to the first floor).

There is no second exam for FSS2020. The next opportunity to retake the project and exam is in HWS2020/2021.

  • Instructors

  • Time and Location

    • Lecture: Wednesday, 10.15 – 11.45, Room A5 6,  B144 (Prof. Dr. Christian Bizer)
    • Exercise 1: Thursday, 10.15 – 11.45, Room B6 26, A104 (RapidMiner, Anna Primpeli)
    • Exercise 2: Thursday, 12.00 – 13.30, Room B6 26, A104 (Python, Ralph Peeters)
    • Exercise 3: Thursday, 13.45 – 15.15, Room B6 26, A104 (Python, Ralph Peeters)

    Note: there are three parallel exercise groups, you are supposed to attend only one.

  • Final exam

    • 75 % written exam
    • 25 % project work (20% report, 5% presentation)
  • Registration

    • For attending the course, please register for the lecture in Portal 2. The course is limited to 80 participants. There will be no “first come – first serve”. Students in higher semesters and students that have failed the course in HWS2019 will be preferred, equally ranked students will be drawn randomly.
    • We offer three alternative times (Thursdays 12.00, 13.45 and 15.30) for the exercise session. Choose one and attend the exercise at the corresponding time (you don't have to register for it).

Lecture Videos, Slides and Exercises



Additional material will be found in the ILIAS group of the course.



Introduction to Data Mining
Introduction to Python (see below table)

Exercise Preprocessing/Visualization

19.02.2020Lecture ClusteringExercise Clustering
26.02.2020Lecture Classification 1Exercise Classification 
04.03.2020Lecture Classification 2Exercise Classification 
11.03.2020Lecture Classification 3Online Exercise Classification 
18.03.2020Video Lecture Association AnalysisOnline Exercise Association Analysis
25.03.2020Video Lecture Text MiningOnline Exercise Text Mining
01.04.2020Video Lecture RegressionOnline Exercise Regression
22.04.2020Introduction to the Student Projects 
and Group Formation
Preparation of Project Outlines
29.04.2020Feedback on Project OutlinesProject Work
06.05.2020Project WorkFeedback on demand
13.05.2020Project WorkFeedback on demand
20.05.2020Submission of project reportPreparation of presentation
27.05.2020Presentation of project resultsPresentation of project results

For all students which are not familiar with Python/Jupyter Notebooks, we offer an introduction on Wednesday, 12 February 2020 between 15:30 and 17:00 in room A5, 6 C 013.