TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Doctorate Of Science
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Learn the characteristics of data. 2) Learn data preprocessing; data mining methods and algorithms. 3) Apply techniques and relevant software on some datasets.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	BİL582 Data Mining
COURSE DEFINITION	Introduction,Getting to know your data,Data preprocessing,Data warehousing and OLAP (Online Analytical Processing),Data cube technology,Associations and correlations: Basic concepts and methods; Advanced topics,Classifications : Basic concepts and methods; Advanced topics,Clustering : Basic concepts and methods; Advanced topics,Outlier detection
COURSE CONTENTS	WEEK TOPICS 1st Week Introduction 2nd Week Getting to know your data 3rd Week Data preprocessing 4th Week Data preprocessing 5th Week Data warehousing and OLAP (Online Analytical Processing) 6th Week Data warehousing and OLAP (Online Analytical Processing) 7th Week Data cube technology 8th Week Mid-term 9th Week Associations and correlations:Basic concepts and methods;Advanced topics 10th Week Associations and correlations:Basic concepts and methods;Advanced topics 11th Week Classifications : Basic concepts and methods; Advanced topics 12th Week Clustering : Basic concepts and methods; Advanced topics 13th Week Outlier detection 14th Week Outlier detection
RECOMENDED OR REQUIRED READING	Han, J., M. Kamber and J. Pei, Data Mining, Elsevier, 2012. Tan, PN. et al., Data Mining, Pearson, 2006. Olson, D. and Y. Shi, Introduction to Business Data Mining,Mc-Graw Hill, 2007.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Project,Lecture,Questions/Answers,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Project 1 30 Total(%) 60 Contribution of In-term Studies to Overall Grade(%) 60 Contribution of Final Examination to Overall Grade(%) 40 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 11 154 Preparation for Final exam 1 69 69 Course hours 14 3 42 Preparation for Midterm exam 1 44 44 Laboratory (including preparation) Final exam 1 2 2 Homework Total Workload 313 Total Workload / 30 10,43 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No