Data Mining II

Important: This is the Web page of the course which took place in FSS 2019. The Web page of the most recent course can be found here.

Building on the Data Mining fundamentals course, this course deepens the theory and practice of advanced data mining topics, such as:

  • Data Preprocessing
  • Regression and Forecasting
  • Dimensionality Reduction
  • Anomaly Detection
  • Time Series Analysis
  • Parameter Tuning
  • Ensemble Methods
  • Deep Learning

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.

Like in the previous years, participants will take part in the annual Data Mining Cup (DMC), an international student competition in data mining, as part of the project work. In addition to the DMC submission, the approaches and results of the project have to be compiled into a written project report, and presented in a plenary session.

Time and Location

Lecture:

  • Tuesday, 13.45 – 15.15,  EO 145 (Schloss Ehrenhof Ost / castle) <- changed!

We'll have two alternatives for the exercise:

  • Exercise: Monday, 10.15 – 11.45, A 5, 6, C012
  • Exercise: Monday, 12.00 – 13.30, A5, 6, C015

Both of these dates are offered, and you have to decide for one.

Final exam

Unlike in the previous years (and unlike, e.g., Data Mining 1), the project is not graded. Your final grade will be based solely and entirely on the final exam.

The exam review for the first exam from FSS2019 will take place on Monday, 19 August, at 8am in B6 C1.01.

The exam review for the second exam from FSS2019 will take place on Thursday, 19 September, at 10am in B6 C1.01.