Ders Planı

CLASS 1

Lesson plan /

Lesson Information

Course Credit
Course ECTS Credit
Teaching Language of Instruction	Türkçe
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?
Course Coordinator	Prof. Dr. RAFET AKDENİZ
Instructor (s)
Course Assistant

Purpose and Content

The aim of the course	The purpose of this course, the pattern discovery and data mining, knowledge discovery in databases is to provide an overview of the theoretical and practical aspects.
Course Content	Course, classes, clusters, association rules, and to discover abnormalities in the data mining algorithms and techniques.

Learning Outcomes

Adequate knowledge in mathematics, physical sciences and the computer engineering subjects of individual branches; the ability to implement theoretical and practical knowledge in the respective areas to modeling and solving computer engineering problems.
Ability to reflect the developments in Information and Communication Technologies to the applications of Information Technology.
Ability to identify, define, formulate and solve complex computer engineering problems; ability to select and implement the appropriate analysis and modeling methods in this respect.
Ability to design experiments for analysing computer engineering problems, to conduct experiments, to collect data, to analyse and interpret the results.
Ability to design a complex informtacis system, process, device or product to meet specific requirements under realistic restrictions and conditions; ability to implement the modern design methods for this purpose.
Ability to use, choose and develop modern techniques and means required for computer engineering applications; ability to use information technologies effectively.
Ability to work effectively in interdisciplinary and multi-disciplinary teams; ability to work individually..
Knowledge of applications in business life like project management, risk management and change management; awareness about entrepreneurship, innovativeness and sustainable development.
Awareness of the necessity of lifelong learning; ability to reach information, follow the latest developments in science and technology; ability to ensure self-renewal perpetually.
Ability to communicate efficiently both in oral and written ways in Turkish; knowledge of at least one foreign language; ability to effectively prepare reports and understand written reports, prepare design and production reports, effective presentation, giving and receiving clear and understandable instructions.
Knowledge on the effects of informatics applications on health, environment and safety in terms of universal and social aspects and information about the problems of the era; awareness on the legal results of informatics solutions.
Acting in line with ethical principles, sense of professional and ethical responsibility; knowledge on the standards of engineering applications.

Weekly Course Subjects

1	A first look at data mining.
2	Knowledge Discovery in Databases.
3	Preparation (Data Merge, reduction, pre-processing, conversion)
4	Analysis of Association Rules
5	Sequential Pattern Analysis
6	Classification and Forecasting - I
7	Classification and Forecasting - II
8	Midterm exam
9	Clustering - I
10	Clustering - II
11	Contrary to the Situation Analysis
12	Web Mining
13	Text Mining
14	Protection of Privacy in Data Mining

Resources

1-1- Han, J. & Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco, Second Edition, 2006.

Yardımcı kaynaklar:

1. Roiger, R.J., & Geatz, M.W., Data Mining: A Tutorial-Based Primer, Addison Wesley, USA, 2003.

2. Dunham, M.H., Data Mining: Introductory and Advanced Topics, Prentice Hall, New Jersey, 2003.

CLASS 1

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Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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