Posted at request of Evgueni Smirnov, Maastrict University ********************************************************************* ** ** ** 8-th SUMMER SCHOOL ON DATA MINING, Maastricht, The Netherlands ** ** http://www.cs.unimaas.nl/datamining/ ** ** ** ** Apologies if you receive multiple copies of this announcement ** ** Please forward to anyone who might be interested ** ** ** ********************************************************************* Summer School: Data Mining An intensive 4-day introduction to methods and applications Department of Knowledge Engineering, Maastricht University, Maastricht, The Netherlands August 30 - September 2, 2010 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 course comes to help. Course Description The course is well balanced between theory and practice. Each lecture is accompanied by a lab in which course 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 course participants develop their own ability to apply data-mining techniques for business and research purposes. Course Description The course focuses on techniques with a direct practical use. A step-by-step introduction to powerful (freeware) data-mining tools will enable you to achieve specific skills, autonomy and hands-on experience. A number of real data sets will be analysed and discussed. In the end of the course you will have your own ability to apply data- mining techniques for research purposes and business purposes. Course Content The course 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 course 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. SIKS Participating in this course is a part of the advanced components stage of SIKS' educational program. SIKS has reserved a number of places for those Ph.D-students working on the course topics. Prerequisites The course 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 course. Registration To register for the course please send an email to the registration office specifying the following information: - Name - University / Organisation - Address - Phone -E-Mail Please register before August 9, 2010 Registration fees Academic fee 600 Euros Non-academic fee 850 Euros Included in the price are: course material and coffee breaks. The local cafeteria will be available for lunch (not included). SIKS-Ph.D. students Participating in this course is a part of the advanced components stage of SIKS' educational program. SIKS has reserved a number of places for those Ph.D-students working on the course topics. SIKS-Ph.D.-students interested in taking the course should NOT contact the local organization, but send an e-mail to office@xxxxxxx and confirm that their supervisor supports their participation E-mail should be sent to: smirnov@xxxxxxxxxxxxxxxxxxxxxxx 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