TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Master's Degree With Thesis
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) Will have learned some basic problems in artificial intelligence and also algorithms for solving them. 2) 2. Will have applied the approaches they have learned for solving at least one artificial intelligence problem.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	There is no recommended optional programme component for this course.
COURSE DEFINITION
COURSE CONTENTS	WEEK TOPICS 1st Week Introduction 2nd Week Intelligent agents 3rd Week Solving problems by searching 4th Week Informed search methods 5th Week Information and reasoning: logical agents 6th Week First-order logic 7th Week Inference in first-order logic 8th Week MIDTERM 9th Week Uncertainty and reasoning 10th Week Uncertainty and reasoning 11th Week Stochastic reasoning systems 12th Week Stochastic reasoning systems 13th Week Making decisions 14th Week Applications/Project presentations
RECOMENDED OR REQUIRED READING	S.J., Ruseel, P. Norvig: Artificial Intelligence: A Modern Approach, Prentice Hall, 2003.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Problem Solving,Other
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 10 Project 1 10 Total(%) 50 Contribution of In-term Studies to Overall Grade(%) 50 Contribution of Final Examination to Overall Grade(%) 50 Total(%) 100
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No