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Credits: SWS : 2+1, Credits 4+2

Participants: Min: 1 Max: 12 Expected: 12

Course type : Seminar

Language: english

Slides etc.

Slides for the introduction can be found here.

Slides from the 2014 Data Mining lecture can be downloaded here.

The seminar templates can be downloaded from here.

The final slide templates can be downloaded here.

The example experimental report can be downloaded here.


You've got Skillz?!? You think you know how to mine data? You want to expand your palette of abilities in the data sciences? Join us in the Advanced Data Challenge!  This seminar will feature interesting real-world data sets, and will require the students to rely on their creativity by finding and utilizing additional data sources to incorporate into their models. Not only will the general the KDD process be emphasized with the application of various models alone or in ensemble or meta-learning techniques, but the finer, forensic, investigative skills necessary for success as a data scientist will be called upon to a significant degree.  The students will work together in teams of two persons. During the semester, students will meet with their seminar advisor every two weeks, they will give one short status updates, hold a final presentation, and write a short paper detailing the work performed.

A sucessful participation of the seminar includes:

  • Presentation (25 min + 5 min Q&A)
  • Written paper (8-10 pages.)


Registration via StudIS required.

Preliminary discussion of the topics: Mo 04/24/2017, 13:30 - 14:30 am in room PZ901