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 basic principles of statistical data analysis 2) Get practice on developing and using PR programs 3) Get ability to PR techniques in problem solving
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Data analysis fundamentals, Feature Reduction, Supervised classification, Perceptron Algorithms,Linear Discriminants,Nearest Neigborhood, Maximum Likelihood Estimation,Bayesian inference, Suppert Vector Machines, Hidden Markov Models, Unsupervised methods, K-means, Hierarchical clustering, Recent challenges
COURSE CONTENTS	WEEK TOPICS 1st Week Data analysis fundamentals 2nd Week Feature Reduction 3rd Week Supervised classification 4th Week Perceptron Algorithms 5th Week Linear Discriminants 6th Week Nearest Neigborhood 7th Week Maximum Likelihood Estimation,Bayesian inference 8th Week Mid-term 9th Week Suppert Vector Machines 10th Week Hidden Markov Models 11th Week Unsupervised methods 12th Week K-means 13th Week Hierarchical clustering 14th Week Recent challenges
RECOMENDED OR REQUIRED READING	Pattern Classification 2nd. Edition., R.O. Duda, P.E. Hart & D.G. Stork, J. Wiley Inc., 2001
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Project
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