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