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)	Associate Professor Selda Güney
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) To know the basic principles of pattern recognition and automatic learning. 2) To know the methods of feature extraction. 3) To develop pattern recognition and machine learning programs and gain an experience. 4) To know how to apply the methods to a specific problem
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION
COURSE CONTENTS	WEEK TOPICS 1st Week Pattern Recognition Basics 2nd Week Feature Selection 3rd Week Nearest Neighborhood 4th Week The Best Prediction 5th Week Bayesian Theorem 6th Week Artificial Neural Networks 7th Week Artificial Neural Networks 8th Week Midterm 9th Week Support Vector Machines 10th Week Support Vector Machines 11th Week Decision Tree Learning 12th Week Applications on Selected Problems 13th Week Applications on Selected Problems 14th Week Applications on Selected Problems
RECOMENDED OR REQUIRED READING	1. Pattern Classification and Machine Learning, Christopher Bishop, Springer. 2. Pattern Classification 2nd Edition, R. O. Duda, P.E. Hart & D.G. Stork Wiley, 2001
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Project
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Assignment 1 25 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 3 3 Preparation for Quiz 0 0 0 Individual or group work 14 8 112 Preparation for Final exam 1 40 40 Course hours 14 3 42 Preparation for Midterm exam 1 30 30 Laboratory (including preparation) 0 0 0 Final exam 1 3 3 Homework 2 35 70 Total Workload 300 Total Workload / 30 10 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No