datamining 2012 - 10th SCHOOL ON DATA MINING

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** 10-th SCHOOL ON DATA MINING, Maastricht University, **
** Maastricht, The Netherlands **
** http://www.unimaas.nl/datamining/ **
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** Apologies if you receive multiple copies of this announcement **
** Please forward to anyone who might be interested **
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School on Data Mining

An intensive 3-day introduction to methods and applications

Department of Knowledge Engineering, Maastricht University,
Maastricht, The Netherlands
October 22 - October 24, 2012


Introduction
Most business organizations collect terabytes of data about business
processes and resources. Usually these data provide just "facts and
figures", not knowledge that can be used to understand and eventually
re-engineer business processes and resources. Scientific community in
academia and business have addressed this problem in the last 20 years
by developing a new applied field of study known as data mining.
In practice data mining is a process of extracting implicit,
previously unknown, and potentially useful knowledge from data. It
employs techniques from statistics, artificial intelligence, and
computer science. Data mining has been successfully applied for
acquiring new knowledge in many domains (like Business, Medicine,
Biology, Economics, Military, etc.). As a result most business
organizations need urgently data-mining specialists, and this is
the point where this school comes to help.


Description
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.


Content
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.


Prerequisites
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.


Certificate
Upon request a certificate of full participation will be provided after
the school.


Registration
To register for the school please send an email to:

smirnov-AT-maastrichtuniversity.nl

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


Registration Deadline: October 15, 2012


Registration fees
Academic fee 600 Euros
Non-academic fee 850 Euros

Coffee breaks are included in the price. The local
cafeteria will be available for lunch (not included).


Registartion e-mail: smirnov-AT-maastrichtuniversity.nl


Regular mail should be sent to:

Evgueni Smirnov
Department of Knowledge Engineering
Faculty of Humanities and Sciences
Maastricht University
P.O.Box 616
6200 MD Maastricht
The Netherlands
Phone: +31 (0) 43 38 82023
Fax: +31 (0) 43 38 84897
E-mail: smirnov-AT-maastrichtuniversity.nl