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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ENM 564DATA MINING3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective To introduce students to basic applications, concepts, and techniques of data mining. To gain experience doing independent study and research.
Course Content This course is statistical data mining, machine learning, and consists of three parts içermektedir.Ders 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 biological research focuses on areas such as the mining areas.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Student apply the basic principles of total quality management to the business systems
2Student solve the business problems by systems approach

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10
LO 0011233255443
LO 0022544444544
Sub Total3777699987
Contribution2444355544

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14228
Assignments51260
Mid-terms13535
Final examination13030
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