COURSE UNIT TITLE

: DATA MINING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DDD 5028 DATA MINING ELECTIVE 3 0 0 4

Offered By

Maritime Security, Safety and Environmental Management

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR BURAK KÖSEOĞLU

Offered to

Maritime Security, Safety and Environmental Management

Course Objective

The aim of this course is to give students the theoretical background of data mining algorithms and techniques and to give the student the ability to select and apply appropriate data mining techniques for different applications. This course will enable a student to learn data preprocessing, association rule mining, classification and prediction, and cluster analysis with applications.

Learning Outcomes of the Course Unit

1   Define basic data mining concepts.
2   Apply preprocessing operations on data.
3   Determine which data mining technique is appropriate to solve a particular problem.
4   Implementations of data mining techniques.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to data mining, basic concepts.
2 Database, Data warehouses.
3 Knowledge Discovery in Databases.
4 Data understanding, Data visualization.
5 Data preparation.
6 Clustering methods, hierarchical clustering.
7 K-means clustering, density based clustering.
8 Midterm Exam.
9 Classification methods, k-nearest neighbor algorithm.
10 Decision trees.
11 Association rule mining.
12 Data mining applications.
13 Data mining applications.
14 Presentation.
15 Presentation.
16 Final Exam.

Recomended or Required Reading

- Han, J. & Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco, Second Edition, 2006.
- Roiger, R.J., & Geatz, M.W., Data Mining: A Tutorial-Based Primer, Addison Wesley, USA, 2003.
- Dunham, M.H., Data Mining: Introductory and Advanced Topics, Prentice Hall, New Jersey, 2003.

Planned Learning Activities and Teaching Methods

Presentation and Applications.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Active participation of students.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assist. Prof. Dr. Cpt. Burak Köseoğlu
burak.koseoglu@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Tutorials 2 3 6
Preparations before/after weekly lectures 14 2 28
Preparing presentations 1 8 8
Preparation for midterm exam 1 10 10
Preparation for final exam 1 10 10
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 102

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.135555
LO.2355553
LO.3355553
LO.433533

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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