COMPUTER ENGINEERING (ENGLISH, NON-THESIS)
Master	TR-NQF-HE: Level 7	QF-EHEA: Second Cycle	EQF-LLL: Level 7

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
CMP6160	Advanced Topics in Artificial Intelligence	Fall	3	0	3	9

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Departmental Elective
Course Level:
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi TEVFİK AYTEKİN
Course Lecturer(s):	Prof. Dr. NAFİZ ARICA
Recommended Optional Program Components:	None
Course Objectives:	This is a research oriented course. Topics vary from one offering to the next. Selected state of the art research papers from various fields of artificial intelligence (such as searching, knowledge representation, learning, probabilistic reasoning, and natural language processing) will be read. Students are required to write paper reviews and do a final project.

Learning Outcomes

The students who have succeeded in this course;
I. Become familiar with current research topics in artificial intelligence
II. Be able to critically read a scientific paper
III. Be able to write a paper review
IV. Be able to present scientific papers
V. Be able to conduct a research in artificial intelligence

Course Content

Complexity; NP-completeness; 3-SAT; NP-compleness proofs; approximation algorithms; randomization; undecidability; halting problem; Rice's theorem.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction
2)	Paper assignments
3)	Review of current literature
4)	Review of current literature
5)	Paper presentations and discussion.
6)	Paper presentations and discussion.
7)	Paper presentations and discussion.
8)	Paper presentations and discussion.
9)	Paper presentations and discussion.
10)	Paper presentations and discussion.
11)	Paper presentations and discussion.
12)	Paper presentations and discussion.
13)	Project presentations
14)	Project presentations

Sources

Course Notes / Textbooks:	NA
References:	Yok - None

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 20
Presentation	1	% 10
Project	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 30
PERCENTAGE OF FINAL WORK		% 70
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	3	14	42
Presentations / Seminar	14	5	70
Project	14	5	70
Final	1	12	12
Total Workload			194

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Define and manipulate advanced concepts of Computer Engineering
2)	Use math, science, and modern engineering tools to formulate and solve advenced engineering problems
3)	Notice, detect, formulate and solve new engineering problems.
4)	Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
5)	Follow, interpret and analyze scientific researches in the field of engineering and use the knowledge in his/her field of study
6)	Work effectively in multi-disciplinary research teams
7)	Acquire scientific knowledge
8)	Find out new methods to improve his/her knowledge.
9)	Effectively express his/her research ideas and findings both orally and in writing
10)	Defend research outcomes at seminars and conferences.
11)	Prepare master thesis and articles about thesis subject clearly on the basis of published documents, thesis, etc.
12)	Demonstrate professional and ethical responsibility.
13)	Develop awareness for new professional applications and ability to interpret them.