Photo credit: Anna Logue

Data Mining II

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, A1.04 <- might be 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

  • 60 % written exam
  • 40 % project work

Exam Review

  • The exam review for the first and second exam from FSS2018 will take place on : Thursday, September 27th, 9am, in room C1.01 (building B6, 26).