INFORMATION TECHNOLOGIES (MASTER) (WITH THESIS) (ENGLISH)
Qualification Awarded	Program Süresi	Toplam Kredi (AKTS)	Öğretim Şekli	Yeterliliğin Düzeyi ve Öğrenme Alanı
Master's ( Second Cycle) Degree	2	120	FULL TIME	TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 7 QF-EHEA:Second Cycle TR-NQF-HE, ISCED (1997-2013): 44,46,48,52,72

Ders Genel Tanıtım Bilgileri

Course Code:

3000004005

Ders İsmi:

Game Programming

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Labs	Credit	ECTS
3	0	0	3	6

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Other Recommended Topics for the Course:

Type of course:

Department Elective

Course Level:

Master

TR-NQF-HE:7. Master`s Degree

QF-EHEA:Second Cycle

EQF-LLL:7. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Prof. Dr. Haluk GÜMÜŞKAYA

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of this course is to demonstrate the basic elements of C# programming language and game programming on the Unity game engine and to bring the student to the point where he can quickly prepare game prototypes by starting and finishing a small game from the design stage.
Course Content:	History of games and game engines, C# programming language, vaariables, loops, collections, functions, classes, object oriented programming, game design and documentation, Unity game engine and its features, data-oriented design, Entitas, Unity DOTS, design and programming exercises.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	History of games and game engines, introduction to C# programming language
2)	Variables and Unity components
3)	Loops and collections, functions
4)	Classes, object-oriented programming
5)	Object oriented programming
6)	Game design and documentation
7)	Unity features and packages
8)	Unity features and packages
9)	Unity features and packages
10)	Data oriented design
11)	Entitas
12)	Unity DOTS
13)	Unity DOTS
14)	Design and programming exercises
15)	Design and programming exercises

Sources

Course Notes / Textbooks:	Introduction to Game Design, Prototyping, and Development: From Concept to Playable Game with Unity and C#, Jeremy Gibson Bond, Addison-Wesley, 2022. Hands-On Unity 2022 Game Development, Nicolas Alejandro Borromeo, Packt, 2022.
References:

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları
Program Outcomes
1) Ability to use and apply current technical concepts and practices in the information technologies of software engineering, data management and computer security.
2) Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems.
3) Ability to use data structures and develop algorithms.
4) Ability to analyze and interpret complex big data systems.
5) Ability to interpret and apply concepts and algorithms in machine learning.
6) Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory.
7) Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics.
8) Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems.
9) Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications.
10) Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools.
11) Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications.
12) Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values.

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	Ability to use and apply current technical concepts and practices in the information technologies of software engineering, data management and computer security.
2)	Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems.
3)	Ability to use data structures and develop algorithms.
4)	Ability to analyze and interpret complex big data systems.
5)	Ability to interpret and apply concepts and algorithms in machine learning.
6)	Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory.
7)	Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics.
8)	Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems.
9)	Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications.
10)	Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools.
11)	Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications.
12)	Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values.

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 20
Project	1	% 50
Semester Final Exam	1	% 30
total		% 100
PERCENTAGE OF SEMESTER WORK		% 70
PERCENTAGE OF FINAL WORK		% 30
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Project	1	100	100
Homework Assignments	2	15	30
Final	1	10	10
Total Workload			185