COURSE UNIT TITLE

: INTRODUCTION TO DATA MINING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CME 4416 INTRODUCTION TO DATA MINING ELECTIVE 2 2 0 6

Offered By

Computer Engineering (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR GÖKSU TÜYSÜZOĞLU

Offered to

Computer Engineering (English)

Course Objective

The aim of this course is to provide an overview for pattern discovery in the field of data mining and knowledge discovery in databases (KDD) from both a theoretical and practical point of view. This course includes data mining algorithms and techniques for the discovery of classes, clusters, association rules and abnormalies.

Learning Outcomes of the Course Unit

1   Describe basic data mining concepts
2   Make data preprocessing operations
3   Solve a particular problem by data mining approaches (classification, clustering, association rule mining etc.)
4   Apply data mining techniques on given dataset
5   Develop a solution for subtopics of data mining (web mining, text mining)

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 First View: Data Mining
2 Knowledge Discovery in Databases
3 Data Preparation (Data Integration, Reduction, Preprocessing, Transformation)
4 Association Rule Mining
5 Sequential Pattern Mining
6 Classification and Prediction - I
7 Classification and Prediction - II
8 Clustering - I
9 Clustering - II
10 Outlier Detection
11 Web Mining
12 Text Mining
13 Privacy Preserving Data Mining
14 Project Presentations

Recomended or Required Reading

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

Complementary Book:
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

Planned Learning Activities and Teaching Methods

Lectures / Presentation
Guided problem solving
Lab exercises
Project

Assessment Methods

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


Further Notes About Assessment Methods

None

Assessment Criteria

All learning outcomes will be evaluated by midterm exam, homework and final exam.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Asst. Prof. Dr. Göksu TÜYSÜZOĞLU
Dokuz Eylul University
Department of Computer Engineering
Tinaztepe Campus 35160 BUCA/IZMIR
Tel: (232) 412 74 40
E-mail: goksu@cs.deu.edu.tr

Office Hours

Tuesday 13:00 - 15:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 17 17
Preparation for final exam 1 19 19
Preparing assignments 1 30 30
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 142

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.144
LO.2443
LO.345334
LO.44434
LO.54534

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

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