DEPARTMENT OF INDUSTRIAL ENGINEERING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1411002017

Ders İsmi:

Artificial Intelligence

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Department Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi Elif TARAKÇI

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of the course is to provide students with information on basic techniques and methods inartificial intelligence and to enable students to have the ability to use artificial intelligence methodsin solving practical problems
Course Content:	Basic concepts and methods of artificial intelligence. Problem solving using artificial intelligence;search methods using and not using problem information. Local search methods and simulated annealing algorithm. Meta-heuristic algorithms. Introduction to artificial neural networks. GameProblems. Prolog programming language, information representation and logical inference.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Intelligent agents have knowledge of search methods, informed and uninformed search methods in solving problems.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) Gains knowledge about the basic methods in the field of artificial intelligence.
2) Gains the ability to formulate and solve practical problems using basic methods in the field of artificialintelligence.
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Basic Concepts, Artificial Intelligence history and philosophy	Lecture Notes
2)	Clever Agents	Lecture Notes
3)	Introduction to Problem Solving and Search Algorithms with Artificial Intelligence	Lecture Notes
4)	Search Algorithms That Don't Use Problem Information	Lecture Notes
5)	Intuitive Search	Lecture Notes
6)	Game Problems	Lecture Notes
7)	Meta-Heuristic Search Methods	Lecture Notes
8)	MidTerm
9)	Artificial neural networks	Lecture Notes
10)	Knowledge-Based Agents	Lecture Notes
11)	First Order Logic	Lecture Notes
12)	Inference in First Order Logic	Lecture Notes
13)	Prolog Programming Language and Logical Programming	Lecture Notes
14)	Prolog Programming Language and Logical Programming	Lecture Notes
15)	Probabilistic Inference	Lecture Notes
16)	Final Exam

Sources

Course Notes / Textbooks:	Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall,Second Edition
References:	Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall,Second Edition Yapay zekâ : bütünleşik bilişe doğru / Ali Orhan Aydın Russell & Norvig, AI: A Modern Approach, 3rd Ed

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	1
Program Outcomes
1) Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.
2) Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3) Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4) Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5) Awareness of the sectors and the ability to prepare a business plan.
6) Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7) Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8) Information about current engineering practices and standards used in engineering practices.
9) The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10) The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.
11) The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12) Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.
13) Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14) In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15) Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.
2)	Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3)	Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4)	Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5)	Awareness of the sectors and the ability to prepare a business plan.
6)	Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7)	Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8)	Information about current engineering practices and standards used in engineering practices.
9)	The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10)	The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.
11)	The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12)	Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.
13)	Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14)	In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15)	Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems

Öğrenme Etkinliği ve Öğretme Yöntemleri

Anlatım
Course

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Semester Final Exam	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	3	42
Midterms	1	2	2
Final	1	2	2
Total Workload			88