Goal of a proseminar is the independent preparation and presentation of a scientific topic, learning and practicing of presentation skills, giving a high-quality presentation and participating in scientific talks via Q&A sessions. Emphasis is on the presentation of the topic to keep the audience engaged while communicating (complex) scientific/ technical information.

Organisation top
The course is organized into two parts.
  • Part 1: Introduction to the proseminar, presentation of the topics to be covered and basic presentation techniques.
  • Part 2: Each participant should prepare a presentation of a selected topic (from the list above), followed by a short Q&A session. After the presentation, the participant will receive feedback from her peers and from the lecturers. In addition to the presentation, a short report has to be prepared. The final grade depends on the presentation, report and overall participation in the class.
Instructors: Language:
  • English
  • Multimedia Room (1526), Appelstraße 9a, 15th floor

For announcements and up-to-date information, please check the Stud.IP page.

Topics top

This proseminar focuses on popular data mining algorithms. The selection of the algorithms has been inspired by the ICDM 2008 paper "Top 10 algorithms in data mining" (PDF). Although the goal of the proseminar is not to cover all aspects of an algorithm, still the presentation should be technically sound and cover the basics of the algorithm.

Below is a list of 16 algorithms to be presented during the proseminar:

Schedule top

1. Introductory Lecture

  • Date: Friday, April 12, 2019
  • Time: 12:30-14:00

2. Presentation Techniques

  • Date: Friday, April 26, 2019
  • Time: 12:30-14:00

3. Student Presentations (ID3, C4.5)

  • Date: Friday, May 17, 2019
  • Time: 12:30-14:00

4. Student Presentations (Random Forest, AdaBoost)

  • Date: Friday, May 24, 2019
  • Time: 12:30-14:00

5. Student Presentations (PageRank, Spreading Activation)

  • Date: Friday, May 31, 2019
  • Time: 12:30-14:00

6. Student Presentations (k-NN, Naïve Bayes)

  • Date: Friday, June 7, 2019
  • Time: 12:30-14:00

7. Student Presentations (k-means clustering, k-medoids)

  • Date: Friday, June 21, 2019
  • Time: 12:30-14:00

8. Student Presentations (Logistic regression, CART, SVM)

  • Date: Friday, July 5, 2019
  • Time: 12:00-14:00

9. Student Presentations (Multilayer perceptron,Apriori, DBSCAN)

  • Date: Friday, July 12, 2019
  • Time: 12:00-14:00
Extra Material top

For giving a good presentation:

For writing in (computer) science:

For further literature search: