DATA AND TEXT MINING PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
IBY324	DATA AND TEXT MINING	6	4	2	8

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	, TYY: + , EQF-LLL: , QF-EHEA:
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit
Instructor(s) of the Course Unit	Assist.Prof. BİLGE TURP GÖLBAŞI
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 Reading	Fields of application of data mining	Lecture, Discussion, Practice
3	Literature Reading	Introducing ready programs in data mining- Electronic statement programs in data mining	Lecture, Discussion, Practice
4	Literature Reading	Preparing the data for analysis (steps)	Lecture, Discussion, Practice
5	Literature Reading	OLAP	Lecture, Discussion, Practice
6	Literature Reading	Classification and clustering	Lecture, Discussion, Practice
7	Literature Reading	Decision Trees	Lecture, Discussion, Practice
8	-	MID-TERM EXAM	-
9	Literature Reading	Statistics in data mining	Lecture, Discussion, Practice
10	Literature Reading	Artificial intelligence in data mining	Lecture, Discussion, Practice
11	Literature Reading	Artificial neural networks in data mining	Lecture, Discussion, Practice
12	Literature Reading	Association rules	Lecture, Discussion, Practice
13	Literature Reading	Other mining techniques in data mining - Web and text mining	Lecture, Discussion, Practice
14	Literature Reading	Case Studies	Lecture, Discussion, Practice
15	Literature Reading	Industrial applications in data mining	Lecture, Discussion, Practice
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Ozkan, Y. (2016). Veri Madenciligi, Istanbul: Papatya.
Oguzlar, A. (2011). Temel Metin Madenciligi, Dora.
Tan, P., Steinbach, M., Kumar, V. (2005). Introduction to Data Mining, Pearson Edition.

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	Interpret the basic concepts, theories and approaches of business information management, programming and management information systems.						5
2	Explain concepts related to field by associating them with information systems and programming languages.					4

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Explain current information about the field with information and communication theories.						5
2	Relate the information and facts about his/her field with other areas of social sciences.					4

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Prepare the technical infrastructure and content of information management in businesses.						5
2	Integrate the theoretical knowledge about the field into today's technology					4

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the programming languages for the functioning of business.						5
2	Interpret the theoretical and practical information they obtained in their field.					4

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill his/her duties and responsibilities related to the solution of problems arising in enterprises.						5
2	Conducts projects related with his/her field.						5

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Integrate the technical information and approaches about his/her field to business management information processes.						5
2	Research on scientific, sectoral developments and innovations related to the field with lifelong learning as a principle.					4

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Cooperates with stakeholders in order to generate new ideas.					4
2	Organize projects and activities for the social environment with social responsibility consciousness and to be able to apply those.					4

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Students will be able to apply knowledge and skills related to his / her field by taking into account his legal, social and ethical responsibilities.					4
2	Write programs by using the programming languages related with his/her field.						5

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	6	78
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	1	1
Preparation for the Final Exam	6	7	42
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	7	6	42
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	42	0	206