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Data Mining (HWS 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 FSS 2020 edition of this course is found in the lecture archive.

Corona Update

The lectures and exercises of this course, as well as the project presentations, will be conducted online via Zoom. If possible, we will provide lecture recordings. For the moment, the exam is planned to be conducted on campus.


Exam Review

The exam review for the exam of FSS2020 will take place on Friday, October 9th 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, WIM-ZOOM-02
    • Exercise 1: Thursday, 10.15 - 11.45, WIM-ZOOM-02
    • Exercise 2: Thursday, 12.00 - 13.30, WIM-ZOOM-02
    • Exercise 3: Thursday, 13.45 - 15.15, WIM-ZOOM-02

    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 FSS2020 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

Slides and exercise assignments will be posted here.

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


 Since the autumn term 2020 starts later due to the Corona pandemic, we'll have a slightly condensed lecture period.

Week Wednesday Thursday

Lecture: Introduction to Data Mining

Exercise: Introduction to Python / RapidMiner

05.10.2020 Lecture: Clustering Exercise: Introduction
12.10.2020 Lecture: Classification 1 Exercise: Clustering
19.10.2020 Lecture: Classification 2 Exercise: Classification 1
26.10.2020 Kick off group projects Exercise: Classification 2
02.11.2020 Lecture: Regression Project feedback
09.11.2020 Project feedback Exercise: Regression
16.11.2020 Lecture: Text Mining Project feedback
23.11.2020 Project feedback Exercise: Text Mining
30.11.2020 Lecture: Association Analysis Results Presentation

Important dates for the group projects:

  • Monday, November 2nd, 23:59: Submission of project proposals
  • Friday, December 23rd, 23:59: Submission of final reports