Course Information

Course Name	Turkish	Veri Madenciliği
	English	Data Mining
Course Code	BBL 606	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		Turkish
Course Coordinator		Şule Öğüdücü
Course Objectives		To introduce students to basic applications, concepts, and techniques of data mining. To gain experience doing independent study and research.
Course Description		Introduction to Data Mining. Survey of data mining applications, techniques and models. Data mining steps: Define goal, data cleaning, data selection and preprocessing, data reduction and data transformation, select data mining algorithm, model assessment, interpretation. Exploration of data mining algorithms: decision trees, regression, association rules, memory based methods, k-nearest neighbor method, clustering, artificial neural networks.
Course Outcomes
Pre-requisite(s)
Required Facilities
Other
Textbook		Jiawei Han and Micheline Kamber (2006). Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers. ISBN 1-55860-489-8.
Other References		Margaret Dunham (2002). Data Mining: Introductory and Advanced Topics. Prentice Hall. ISBN 0130888923. David J. Hand, Heikki Mannila, and Padhraic Smyth (2001). Principles of Data Mining. MIT Press. ISBN 026208290X. Pang-Ning Tan, Michael Steinbach, Vipin Kumar (2005). Introduction to Data Mining. Addison Wesley, ISBN: 0-321-32136-7