COURSE UNIT TITLE

: STATISTICAL METHODS IN DATA MINING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4138 STATISTICAL METHODS IN DATA MINING ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR NESLIHAN DEMIREL

Offered to

Statistics
Statistics(Evening)

Course Objective

This course aims to learn students the data mining concept, statistical methods used in data mining and to apply these methods to address different data mining goals and to real-world problems.

Learning Outcomes of the Course Unit

1   Describing the concepts of data mining
2   Explaining supervised and unsupervised learning
3   Using data preparations
4   Using of clustering, classification, regression and association rule algorithms
5   Comparing properties of algorithms
6   Using data mining softwares
7   Evaluating models and results

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 and Data Mining Concepts
2 Data Preprocessing
3 Supervised Learning (Regression): Basic Concepts and Algorithms
4 Supervised Learning (Regression): Algorithms
5 Supervised Learning (Regression): Algorithms and Model Evaluation
6 1. Project Presentations
7 Supervised Learning (Classification): Basic Concepts and Algorithms
8 Supervised Learning (Classification): Algorithms
9 Supervised Learning (Classification): Algorithms and Model Evaluation
10 2. Project Presentations
11 Unsupervised Learning (Clustering): Basic Concepts and Algorithms
12 Unsupervised Learning (Clustering): Algorithms and Model Evaluation
13 Unsupervised Learning (Association Rules): Basic Concepts and Algorithms
14 3. Project Presentations

Recomended or Required Reading

Textbook(s):
Han, J., Pei, J., Tong, H. (2023). Data Mining: Concepts and Techniques. 4th Ed., Morgan Kaufmann Publishers.
Supplementary Book(s):
1. Larose, D.T., Larose, C.D. (2014). Discovering Knowledge In Data: An Introduction to Data Mining. John Wiley and Sons Inc.
2. Alpaydın, E. (2020). Introduction to Machine Learning. 4th Ed. The MIT Press.
3. Gareth, J., Daniela, W., Trevor, H., & Robert, T. (2023). An introduction to statistical learning: with applications in R. 2nd Ed., Spinger.

Planned Learning Activities and Teaching Methods

Lectures, projects, case studies and PC laboratory exercises.

Assessment Methods

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


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams and projects.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at https://fen.deu.edu.tr/en/

Contact Details for the Lecturer(s)

DEU Faculty of Sciences Department of Statistics
e-mail: neslihan.ortabas@deu.edu.tr
Phone:+90 232 301 86 00

Office Hours

Send an e-mail for a meeting request.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 8 2 16
Preparation for midterm exam 1 10 10
Preparation for final exam 1 15 15
Project Preparation 3 10 30
Final 1 2 2
Project Assignment 3 2 6
Midterm 1 2 2
TOTAL WORKLOAD (hours) 123

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555
LO.6555
LO.7554532

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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