DATA MINING PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
BIL421	DATA MINING	5	3	3	6

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Elective
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. OĞUZHAN ÖZTAŞ
Instructor(s) of the Course Unit	Assist.Prof. ABDULLAH SEVİN-Assist.Prof. OĞUZHAN TAŞ
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of this course is to teach the concepts of Data Mining, Data Preparation, Techniques, Statistical Learning Theory (Naive Bayes), Clustering Methods (K-Means, Hierarchical), Decision Trees and Decision Rules, and Association Rules.
Contents of the Course Unit:	This course covers topics related to extracting useful information from data in line with the objectives of data mining, using discovered knowledge to help explain the current state, and predicting future occurrences.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Understand the fundamental concepts of Data Mining.
Be able to apply Data Mining techniques.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Introduction	-
2	-	Data Mining and Data Warehouse - Database	-
3	-	Data Mining and Data Warehouse - Data Warehouse	-
4	-	Data Mining Process and Applications	-
5	-	Data Mining Methods	-
6	-	Classification with Decision Trees	-
7	-	Classification with Decision Trees	-
8	-	MID-TERM EXAM	-
9	-	Classification with Decision Trees	-
10	-	Classification and Regression Trees	-
11	-	Classification with K-Nearest Neighbor Algorithm	-
12	-	Naive Bayes Classifiers	-
13	-	Classification with Support Vector Machines	-
14	-	Clustering	-
15	-	Association Rules	-
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Lecture Notes

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	30
Homework Assessment	1	10
Short Exam	1	10
Final Exam	1	50
Mid-Term Exam	1	30
Practice	1	15
Short Exam	1	5
Final Exam	1	50
TOTAL	8	200

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Explains the fundamental engineering concepts of computer science and relates them to the groundwork of computer science.						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Uses theoretical and practical knowledge coming from mathematics, probability, statistics and various other branches of life sciences, to find solutions to engineering problems.			2

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Determines the components and the underlying process of a system and designs an appropriate computational model under reasonable constraints.					4
2	Designs a computer-aided conceptual model with modern techniques.			2

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Determines, detects and analyzes the areas of computer science applications and develops appropriate solutions.				3
2	Identifies, models and solves computer engineering problems by applying appropriate analytical methods.					4
3	Determines and uses the necessary information technologies in an efficient way for engineering applications.	0

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Possess the responsibility and ability to design and conduct experiments for engineering problems by collecting, analyzing and interpreting data.				3
2	Possess the ability to conduct effective individual study.			2
3	Takes responsibility as a team work and contributes in an effective way.			2

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Monitors the developments in the field of information technologies by means of internet and related journals and possess the required knowledge for the management, control, development and security of information technologies.					4
2	Develops positive attitude towards lifelong learning.				3

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Communicates effectively by oral and/or written form and uses at least one foreign language.			2
2	Possess sufficient consciousness about the issues of project management, practical applications and also environmental protection, worker's health and security.				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Possess professional and ethical responsibility and willingness to share it.				3
2	Possess sufficient consciousness about the universality of engineering solutions and applications and be well aware of the importance of innovation.				3

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	14	1	14
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	2	2
Preparation for the Final Exam	1	35	35
Mid-Term Exam	1	2	2
Preparation for the Mid-Term Exam	1	30	30
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	32	0	125