Software Engineering (English) Preview
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course General Introduction Information

Course Code:

COE308

Course Name:

Introduction to Artificial Intellegence

Course Semester:

Spring

Course Credits:

ECTS

Language of instruction:

Course Requirement:

Does the Course Require Work Experience?:

Type of course:

Necessary

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 :

Assoc. Prof. HATİCE ESRA ÖZKAN UÇAR

Course Lecturer(s):

Prof. Dr. Halis ALTUN

Course Assistants:

Course Purpose and Content

Course Objectives:	The aim of this course is to provide students the knowledge about the basic techniques and methodologies of artificial intelligence and abilities to apply artificial intelligence methods on practical problems.
Course Content:	Basic concepts and techniques of AI. Problem solving in AI, informed and uninformed search techniques, Local search techniques and simulated annealing. Meta-heuristic search methods. Introduction to Neural Networks. Game playing, Prolog overview, knowledge representation and reasoning.

Learning Outcomes

The students who have succeeded in this course;
1) Knowledge about the basic methodologies in artificial intelligence.,
2) Ability to use knowledge to formulate, and solve practical problems using artificial intelligence techniques.

Course Flow Plan

Week	Subject	Related Preparation
1)	Introductory terms, foundations, history and philosophy of AI	-
2)	Intelligent Agents	-
3)	Problem Solving and Introduction to Search Methods	-
4)	Uninformed Search Methodologies	-
5)	Heuristic Search	-
6)	Game Playing	-
7)	Meta-Heuristics	-
8)	Neural Networks	-
9)	Knowledge Based Agents	-
10)	First Order Logic	-
11)	Inference in First Order Logic	-
12)	Prolog and Logic Programming	-
13)	Prolog and Logic Programming	-
14)	Probabilistic Reasoning	-

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.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Medium	3 Highest

	Program Outcomes	Level of Contribution
1)	Sufficient knowledge in mathematics, science and software engineering discipline-specific topics; the theoretical and practical knowledge in these areas, the ability to use in complex engineering problems.
2)	The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modelling methods for this purpose.
3)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools necessary for analysis and solution of complex problems in engineering applications; ability to use information technologies effectively.
5)	Ability to design experiments, conduct experiments, collect data, analyse and interpret the results of complex engineering problems or discipline-specific research topics.
6)	Disiplin içi ve çok disiplinli takımlarda etkin biçimde çalışabilme becerisi; bireysel çalışma becerisi.
7)	Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
8)	Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give clear and understandable instructions and to receive.
9)	Conformity to ethical principles, professional and ethical responsibility; Information on standards used in engineering applications.
10)	Information on practices in business, such as project management, risk management and change management; awareness about entrepreneurship, innovation; information on sustainable development.
11)	Information on the effects of engineering applications on health, environment, and safety in universal and social dimensions, and on the problems of the modern age in engineering; awareness of the legal consequences of engineering solutions.
12)	Adequate skills in the analysis, design, verification, evaluation, implementation, implementation, and maintenance of software systems

Learning Activity and Teaching Methods

Alan Çalışması
Anlatım
Beyin fırtınası /Altı şapka
Bireysel çalışma ve ödevi
Course
Grup çalışması ve ödevi
Labs
Homework
Problem Çözme
Uygulama (Modelleme, Tasarım, Maket, Simülasyon, Deney vs.)

Measurement and Evaluation Methods and Criteria

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Sözlü sınav
Homework
Uygulama
Bireysel Proje
Grup Projesi
Sunum

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Application	2	% 30
Midterms	1	% 30
Final	1	% 40
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Aktiviteye Hazırlık	Aktivitede Harçanan Süre	Aktivite Gereksinimi İçin Süre	Workload
Course Hours	10	5			50
Application	3	9			27
Homework Assignments	2	24			48
Midterms	1	24			24
Final	1	24			24
Total Workload					173