DATA AND TEXT MINING PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YBS208	DATA AND TEXT MINING	4	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 :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	This course aims to introduce and promote the use of data mining. This course aims to gain the ability to analyze large-scale databases.
Contents of the Course Unit:	Contents of the course include the subjects such as basics of data mining in terms of statistical, machine learning and database. The course consists of three sections. The first section is about the basics of statistics and machine learning approach for data mining. In section two, basic data mining and algorithms for Online Analytical Processing, relationship rules and grouping will be covered. The third and last section of the course focuses on researches in areas such as text mining, association filter, link analysis.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Use data mining software.
Describe basket analysis and rules of association.
Apply grouping algorithms on cases.
Analyze classification algorithms.
Conclude from the analysis results of classification algorithms.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Introduction and General Concepts	Lecture & Discussion & Practice
2	Literature Review	Data mining fields of application	Lecture & Discussion & Practice
3	Literature Review	Ready programs in data mining - Electronic Table Programs in data mining	Lecture & Discussion & Practice
4	Literature Review	Preparing data analysis (steps)	Lecture & Discussion & Practice
5	Literature Review	OLAP	Lecture & Discussion & Practice
6	Literature Review	Classification and Clustering	Lecture & Discussion & Practice
7	Literature Review	Decision Trees	Lecture & Discussion & Practice
8	-	MID-TERM EXAM	-
9	Literature Review	Statistics in Data Mining	Lecture & Discussion & Practice
10	Literature Review	Artificial Intelligence in Data Mining	Lecture & Discussion & Practice
11	Literature Review	Artificial Neural Networks in Data Mining	Lecture & Discussion & Practice
12	Literature Review	Association theories	Lecture & Discussion & Practice
13	Literature Review	Other mining theories in Data mining -Web ve Text Mining	Lecture & Discussion & Practice
14	Literature Review	Case Studies	Lecture & Discussion & Practice
15	Literature Review	Industrial Applications in data mining	Lecture & Discussion & Practice
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Ozkan, Y. (2016). Veri madenciligi yontemleri. Papatya Publications Egitim.
Oguzlar, A. (2011). Temel metin madenciligi. Dora Publications.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define concepts such as management, manager and leader.					4
2	Analyze the accuracy, reliability and validity of the new information obtained from the data.						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Report the obtained data.						5
2	Prepare software and projects related with the field.						5

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the appropriate resources for data analysis related with the field.						5
2	Analyze the work processes.						5

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Manage projects as part of a team.						5
2	Apply the material, techniques and analyzes in relation with the subject for project and work flows.						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill responsibility with a focus on result in individual and team studies.						5

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Recognizes what he/she knows about his/her field or not.						5
2	Act the theoretical knowledge in real life with learning to learn approach.						5
3	Apply different methods and techniques with an innovative approach in his/her research.						5

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the results obtained in accordance with voluntarism and social responsibility projects.						5
2	Establish a healthy contact with colleagues				3
3	Share the analyzes and obtained results with colleagues.				3
4	Cooperate with colleagues at international level with the help of foreign language competency.				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Behave in accordance with ethical values regarding the collection, analysis and reporting of data.					4
2	Participate the design of work processes and systems with full quality.						5
3	Cooperate with other employees for the continuation of sustainability in the profession.					4

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	13	2	26
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	6	2	12
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	1	1
Preparation for the Final Exam	7	5	35
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	6	6	36
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	48	0	153