Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
4DOT206Artificial İntelligence1+2+02522.04.2026

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Digital Game Design
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The aim of this course is to teach students the historical, philosophical, mathematical, and computational foundations of Artificial Intelligence (AI). Students will explore the concept of AI, human-computer interaction, and key technologies such as artificial neural networks, machine learning, deep learning, and natural language processing. They will also gain in-depth knowledge about AI applications, computer vision, generative AI, and the role of AI in digital games. By the end of the course, students will be able to apply AI techniques both theoretically and practically.
Course Content This course will begin by introducing the historical and philosophical origins of AI, followed by its mathematical and computational foundations. The AI concept and its relationship with human-computer interaction will be discussed. Topics covered will include artificial neural networks, machine learning, deep learning, natural language processing, computer vision, and generative AI. Generative AI and its applications, along with its role in digital games, will also be explored. The course aims to provide students with practical opportunities, in addition to theoretical knowledge, teaching them how to apply AI techniques in real-world scenarios.
Course Methods and Techniques 1: Theoretical Expression, 2: Drill and Practice, 3: Problem Solving, 4: Question and Answer, 5: Discussion, 6: Demonstration, 7: Study Group, 8: Directed Practice, 9: Brainstorming, 10: Self-Study, 11: Problem Solving, 12: Project Based Learning
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Instructor Kazım Timuçin Utkan
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Nabiyev, V. (2021). Yapay Zeka. İstanbul: Seçkin Yayıncılık.
Course Notes -

Course Category
Engineering Design %50
Field %50

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
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ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 15 1 15
Hours for off-the-c.r.stud 15 4 60
Assignments 10 3 30
Practice 15 2 30
Project 1 2 2
Final examination 1 3 3
Total Work Load   Number of ECTS Credits 5 140

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Understand the historical, philosophical, mathematical, and computational foundations of Artificial Intelligence.
2 Define the concept of Artificial Intelligence and gain knowledge of key components and technologies involved.
3 Comprehend human-computer interaction and the role of AI in this context.
4 Apply AI methods such as artificial neural networks, machine learning, and deep learning in practical scenarios.
5 Gain knowledge about natural language processing, computer vision, and generative AI technologies and their applications.
6 Understand the role of AI in digital games and learn how to implement AI in game development.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Yapay Zekanın Tarihsel ve Felsefi Kökeni - -
2 Mathematical and Computational Origins of Artificial Intelligence. - -
3 The Concept of Artificial Intelligence. - -
4 Human-Computer Interaction. - -
5 Artificial Neural Networks - -
6 Artificial Learning - -
7 Machine Learning. - -
8 Midterms - -
9 Deep Learning. - -
10 Natural Language Processing. - -
11 Computer Vision. - -
12 Generative Artificial Intelligence. - -
13 Applications of Generative Artificial Intelligence. - -
14 Artificial Intelligence and Digital Games - -
15 Finals - -

 
Sustainable Development Goals
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 3 4 5 2 2 1 2 2 1 1 1
C2 2 2 5 2 2 1 2 2 1 1 1
C3 3 3 5 3 3 2 2 1 1 1 1
C4 2 5 5 3 2 2 4 3 1 1 1
C5 2 5 5 3 2 2 4 3 1 1 1
C6 4 4 4 3 4 2 3 2 1 1 1

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  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=237474&curProgID=5728&lang=en