Mobil Teknolojileri
Associate	TR-NQF-HE: Level 5	QF-EHEA: Short Cycle	EQF-LLL: Level 5

General course introduction information

Course Code:

MMOT223

Course Name:

Artificial Intelligence

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Department/Faculty Elective

Course Level:

Associate

TR-NQF-HE:5. Master`s Degree

QF-EHEA:Short Cycle

EQF-LLL:5. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Öğr.Gör. ALPER ÇELTİKÇİ

Course Lecturer(s):

EMEL KOÇ
Öğr.Gör. NİLGÜN İNCEREİS

Course Assistants:

Course Objective and Content

Course Objectives:

* To understand the concept of Artificial Intelligence.
Understanding Software Agents, Heuristic Problem Solving, State Space.
* To learn the methods of searching in the state space, finding the minimum path, modeling the information.
* To know predicate logic, cryptology, encryption methods.
* Learning games, Artificial Intelligence Algorithms.
* To be able to understand Artificial Intelligence Applications.

Course Content:

Artificial Intelligence Concept. Software Agents. Intuitive Problem Solving. State Space. State Space Search. Minimum Path Finding. Modeling of Information. Predictive logic. Cryptology. Encryption Methods. Games. Artificial Intelligence Algorithms. Artificial Intelligence Applications.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Understands the concept of artificial intelligence
2) Understand Software Agents, Heuristic Problem Solving, State Space
2 - Skills
Cognitive - Practical
1) State Space Search, Finding the Minimum Path, Learns the modeling methods.
2) Know predicate logic, cryptology, encryption methods
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
1) Learns Games, Artificial Intelligence Algorithms
2) Understands Artificial Intelligence Applications.
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Introduction to the course	Course Notes
2)	Artificial Intelligence Concept.	Course Notes
3)	Software Agents.	Course Notes
4)	Intuitive Problem Solving.	Course Notes
5)	State Space.	Course Notes
6)	State Space Search.	Course Notes
7)	Minimum Path Finding.	Course Notes
8)	MIDTERM	Course Notes
9)	Modeling of Information. Predictive logic.	Course Notes
10)	Cryptology.	Course Notes
11)	Encryption Methods.	Course Notes
12)	Games.	Course Notes
13)	Artificial Intelligence Algorithms.	Course Notes
14)	Artificial Intelligence Applications.	Course Notes
15)	Final Exam	Course Notes

Sources

Course Notes / Textbooks:	Ders Notları
References:	Course Notes

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4	5	6
Program Outcomes
1) Has basic theoretical and practical knowledge in mathematics, computation and computer science.
2) It implements the defined problems and models of computer science and / or computer science and implements basic solution proposals.
3) Uses algorithmic thinking and planning approach in their applications.
4) Develops software components whose specifications are defined.
5) Communicates spoken and written; at least one foreign language at least on the European Language Portfolio A2 General Level, monitors information in the field of computer science and computer science and communicates with colleagues.
6) The necessity of lifelong learning follows consciousness and current developments in information and communication technologies.
7) Vocational and ethical responsibility is conscious and has an awareness of professional ethics in information applications.
8) It works effectively either individually or on teams.

Course - Learning Outcome Relationship

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

	Program Outcomes	Level of Contribution
1)	Has basic theoretical and practical knowledge in mathematics, computation and computer science.
2)	It implements the defined problems and models of computer science and / or computer science and implements basic solution proposals.
3)	Uses algorithmic thinking and planning approach in their applications.
4)	Develops software components whose specifications are defined.
5)	Communicates spoken and written; at least one foreign language at least on the European Language Portfolio A2 General Level, monitors information in the field of computer science and computer science and communicates with colleagues.
6)	The necessity of lifelong learning follows consciousness and current developments in information and communication technologies.
7)	Vocational and ethical responsibility is conscious and has an awareness of professional ethics in information applications.
8)	It works effectively either individually or on teams.

Learning Activity and Teaching Methods

Brainstorming/ Six tihnking hats
Lesson
Group study and homework
Lab
Homework
Problem Solving
Project preparation
Report Writing
Q&A / Discussion

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Application
Individual Project
Presentation
Reporting
Bilgisayar Destekli Sunum

Assessment & Grading

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

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Project	1	30	30
Homework Assignments	1	10	10
Midterms	1	30	30
Final	1	30	30
Total Workload			145