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SECOND CYCLE - MASTER'S DEGREE
THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
INDUSTRIAL ENGINEERING DEPARTMENT
1261 Industrial Engineering
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
ENM 564
DATA MINING
3 + 0
1st Semester
7,5
COURSE DESCRIPTION
Course Level
Master's 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
1
Student apply the basic principles of total quality management to the business systems
2
Student solve the business problems by systems approach
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
PO 04
PO 05
PO 06
PO 07
PO 08
PO 09
PO 10
LO 001
1
2
3
3
2
5
5
4
4
3
LO 002
2
5
4
4
4
4
4
5
4
4
Sub Total
3
7
7
7
6
9
9
9
8
7
Contribution
2
4
4
4
3
5
5
5
4
4
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
Assignments
4
5
20
Mid-terms
1
60
60
Final examination
1
73
73
Total Work Load
ECTS Credit of the Course
195
7,5
COURSE DETAILS
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All Years
2016-2017 Fall
This course is not available in selected semester.
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L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes