PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
YOBS 528	DATA WAREHOUSE AND DATA MINING	3 + 0	2nd Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The aim of the course is give information about data mining concepts, preparing the data, statistical classification method (naïve bayes), clustering methods(k-means, hierarchical), decision trees and decision rules, association rules.
Course Content	This course is statistical data mining, machine learning, and consists of three parts içermektedir. The course the basics in terms of a data base. The first part of data mining and machine learning approach for the statistical foundations of Online Analytical Processing hakkındadır.İkinci section, for operations such as grouping of association rules, and we will cover the basic data mining algorithms. The last part of the course text mining, association filter, linkage analysis and research focuses on different areas.
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Data mining concepts
2	Preparing the data
3	Statistical classification method (naïve bayes)
4	Clustering methods(k-means, hierarchical), decision trees and decision rules, association rules.

COURSE'S CONTRIBUTION TO PROGRAM

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	3	42
Assignments	2	40	80
Mid-terms	1	13	13
Final examination	1	18	18
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

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