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
BIL 3013 INTRODUCTION TO DATA MINING COMPULSORY 2 2 0 6

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR EFENDI NASIBOĞLU

Offered to

Computer Science

Course Objective

The aim of this course is to enable students to learn the concepts of data mining, to collect data, to prepare data, to analyze the relevant system, and to apply the methods used in data mining to real-world problems for different purposes.

Learning Outcomes of the Course Unit

1   Have a good understanding of data mining concepts
2   Have ability to identify the current system and describe data used in this system
3   Be capable to prepare data for the specific methods
4   Have a good understanding and interpretation of methods used in data mining
5   Evaluate, develope and deploy the project to real life

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 Data collection
3 Database, Data warehouses
4 Knowledge Discovery in Databases
5 Data understanding, Data visualization
6 Data preparation
7 Clustering methods, hierarchical clustering
8 k-means clustering, density based clustering
9 Classification methods, k-nearest neighbor algorithm
10 Decision trees, C4.5, CART
11 Neural Networks, fundamentals
12 Neural Networks - cont'd
13 Model evaluation
14 Data mining applications

Recomended or Required Reading

Textbook(s):
- Han, J. , Kamber, M., Pei, J., Data Mining: Concepts and Techniques. 3rd Ed., Morgan Kaufmann Publishers, 2011
- Larose, Daniel T., Discovering Knowledge In Data An Introduction to Data Mining. New Jersey: John Wiley and Sons Ltd, 2005
Supplementary Book(s):
- Tan, P., Steinbach, M., Kumar, V., Introduction to Data Mining, Addison Wesley, 2006
- Ilker Köse, Veri madenciliği: Teori, Uygulama ve Felsefesi. Papatya Yay. Eğitim, 2018.

Planned Learning Activities and Teaching Methods

The course is taught in the form of lectures and class presentations.

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

Assignments: %30
Midterm exam: %30
Final exam: %40

Language of Instruction

Turkish

Course Policies and Rules

Students will come to the class in time. Attending the 70% of the classes are mandotary.

Contact Details for the Lecturer(s)

efendi.nasibov@deu.edu.tr

Office Hours

Will be announced.

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 3 42
Preparation for midterm exam 1 10 10
Preparation for final exam 1 20 20
Preparing assignments 2 8 16
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 148

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555

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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