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FIRST CYCLE - BACHELOR'S DEGREE
FACULTY OF ECONOMICS & ADMINISTRATIVE SCIENCES
PUBLIC FINANCE DEPARTMENT
208 PUBLIC FINANCE (Evening Classes)
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
YBS 476
DATA MINING
3 + 0
6th Semester
5
COURSE DESCRIPTION
Course Level
Bachelor's Degree
Course Type
Elective
Course Objective
Introducing and teaching data mining with applications.
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
Data Mining Fundemantals
2
Integration data mining with applications
COURSE'S CONTRIBUTION TO PROGRAM
Data not found.
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
Mid-terms
1
20
20
Final examination
1
26
26
Total Work Load
ECTS Credit of the Course
130
5
COURSE DETAILS
Select Year
All Years
2023-2024 Spring
2021-2022 Summer
2020-2021 Summer
Course Term
No
Instructors
Details
2023-2024 Spring
2
HAMİD YEŞİLYAYLA
Details
2021-2022 Summer
1
SELÇUK BURAK HAŞILOĞLU
Details
2020-2021 Summer
1
SELÇUK BURAK HAŞILOĞLU
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Course Details
Course Code
Course Title
L+P Hour
Course Code
Language Of Instruction
Course Semester
YBS 476
DATA MINING
3 + 0
2
Turkish
2023-2024 Spring
Course Coordinator
E-Mail
Phone Number
Course Location
Attendance
Lecturer HAMİD YEŞİLYAYLA
hyesilyayla@pau.edu.tr
İİBF B0213
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Goals
Introducing and teaching data mining with applications.
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.
Topics
Weeks
Topics
1
Introduction to Data Mining
2
Introduction to Data Mining
3
Data Preprocessing
4
Data Warehouses
5
Association Rules
6
Classification 1
7
Classification 1
8
Midterm
9
Time Series Analysis
10
Clustering 1
11
Clustering 2
12
Intrusion Detection
13
Text Mining
14
Web Mining
Materials
Materials are not specified.
Resources
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
60
Final Exam
Midterm Exam
40
Midterm Exam
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