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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 Assist.Prof. BEŞİR TOPALOĞLU
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

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES

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
Total Workload of the Course Unit 153
Workload (h) / 25.5 6
ECTS Credits allocated for the Course Unit 6,0