Our school on data mining tries to find a balance between theory and practice. Each lecture is accompanied by a lab in which participants experiment with the techniques introduced in the lecture. The lab tool is Weka, one of the most advanced data-mining environments. A number of real data sets will be analysed and discussed. In the end of the school participants develop their own ability to apply data-mining techniques for business and research purposes.

The school will cover the topics listed below.

  • The Knowledge Discovery Process
  • Data Preparation
  • Basic Techniques for Data Mining:
    • Decision-Tree Induction
    • Rule Induction
    • Instance-Based Learning
    • Bayesian Learning
    • Support Vector Machines
    • Regression Techniques
    • Clustering Techniques
    • Association Rules
  • Tools for Data Mining
  • How to Interpret and Evaluate Data-Mining Results

Intended Audience
This school is intended for four groups of data-mining beginners: students, scientists, engineers, and experts in specific fields who need to apply data-mining techniques to their scientific research, business management, or other related applications.

The school does not require any background in databases, statistics, artificial intelligence, or machine learning. A general background in science is sufficient as is a high degree of enthusiasm for new scientific approaches.

To register for the school please send an email to:

(due to summer holidays please send the registration to both e-mails)

In the e-mail please specify: Name, University/Organisation, Address, Phone and E-Mail

Registration Deadline: August 23, 2013
Registration Fees:

  • Academic fee 750 Euros
  • Non-academic fee 1000 Euros