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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YBS 476DATA MINING3 + 08th Semester5

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
1Data Mining Fundemantals
2Integration data mining with applications

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

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)14570
Mid-terms177
Final examination11111
Total Work Load

ECTS Credit of the Course






130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Spring2HAMİD YEŞİLYAYLA


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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 %70
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
WeeksTopics
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 MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes