DIGITAL GAME DESIGN
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
GEP0021	Artificial Intelligence and Its Application Areas	Fall	3	0	3	5

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	GE-Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :
Course Objectives:	The objective of this course is to provide the student with a perspective on artificial intelligence terminology, common methods, artificial intelligence applications in the real world and their effects and mis-uses. During the course, the student will learn the most used artificial intelligence algorithms and their applications in case studies, and will brainstorm on weekly discussion topics.

Learning Outcomes

The students who have succeeded in this course;
1) The student will be able to understand what artificial intelligence can and cannot do.
2) The student will be able to explore the applications of artificial intelligence in different fields.
3) Student will be able to apply artificial intelligence solutions to real world problems.
4) The student will be able to discuss artificial intelligence in terms of bias and fairness.
5) The student will be able to understand the effects of artificial intelligence in the real world.

Course Content

In this course, students will learn what artificial intelligence technology is, how it works, and its capabilities. In this course, in which different application areas are discussed comprehensively, students will have the opportunity to evaluate the benefits and difficulties of the application areas through discussion topics. Students will gain a perspective in identifying needs in order to solve real-world problems with artificial intelligence approaches, and will also be involved in discussions about international artificial intelligence ethical principles such as objectivity, transparency, explainability, and accountability. They will have a high awareness to evaluate the processes of application of artificial intelligence in different business areas from start to finish, in general, from technical and social aspects.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	"What is AI? Where do we use AI? Phylosophy of AI; AI in problem solving; Case Study - Chicken Crossing Puzzle Case Study - Towers of Hanoi; Case Study - Tic Tac Toe"""
2)	"AI in Healthcare Predicting health risk; Smart identification and diagnosis; Smart prescription; Smart imaging & segmentation; Personalized healhcare; AI in psychology; Discussion: Chest Xray Classification / Segmentation"
3)	"AI in Entertainment and Gaming Content personalization; Metadata tagging; User engagement; Promotion and advertising Captioning / Subtitle generation; Discussion: In-app purchases"
4)	"AI in Social Media How to organize massive data; Setting trends; Hashtags; Discussion: Using AI to manipulate user choices; Discussion: Using AI for disaster response"
5)	"AI in Security Cyber attacks; Data security; Anti fraud systems; Biometric recognition / verification Know Your Customer (KYC)"
6)	"AI in Finance Insuring, banking, asset management; Cryptocurrency & Crypto banks Algorithmic trading; Financial risk management; Anti-Money Laundering (AML)"
7)	"AI in Travel & Transportation Automated travel services; Traveler behaviors; Personalized travel experience; Logictics route optimization; Warehouse operations"
8)	"AI in Robotics Robotics applications; Robotic packaging; Open source robotics; Robotics in healthcare, agriculture, automative, supply chain, military; Discussion: Robot ethics"
9)	"AI in E-commerce Transforming the shopping experience; Virtual assistants; Addressing consumer needs through deeper insights; Provide personalized or targeted offers; Consumer behavior forecasting; Inventory management; Smart customer service"
10)	"AI in Manifacturing and Business Optimization of supply chain; Optimization of staff, inventory control, energy consumption Optimization of raw material supply; Predictive and prescriptive data analysis; Factory automation; Discussion: What AI can / cannot do"
11)	"AI in Law E-discovery; Expertise automation; Legal search and document management; Contract and litigation document analytics and generation; Predictive analysis"
12)	"Human Centered AI & Ethics AI in non-profit sectors; AI for social good; AI in education; AI in sociology; AI bias and fairness; Misuses of AI; Machine morality - Artificial Moral Agents (AMA); Transparency & Explainability; Discussion: Automation results in unemployment or new opportunities?"
13)	"Adverse uses of AI Adversarial attacks on AI; Possible future adjustments; Discussion"
14)	"Thinking about AI AI and developing economies ; AI Ethics ; AI and jobs ; Social Impacts of AI ; Political Impacts of AI "

Sources

Course Notes / Textbooks:	Artificial Intelligence: A Modern Approach
References:	"50 Soruda Yapay Zeka, Cem Say SuperIntelligence, Nils Nilsson Yapay Zeka Geçmişi Geleceği, Nils Nilsson The Rise of the Robots, Martin Ford Privacy, Eirik Lokke Life 3.0 — Being Human in the Age of Artificial Intelligence, Max Tegmark"

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	4	% 40
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	3	42
Quizzes	4	8	32
Midterms	1	4	4
Final	1	4	4
Total Workload			124

Contribution of Learning Outcomes to Programme Outcomes

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

	Program Outcomes	Level of Contribution
1)	Comprehend the conceptual importance of the game in the field of communication, ability to implement the player centered application to provide design.
2)	Analyze, synthesize, and evaluate information and ideas from various perspectives.
3)	Analyze the key elements that make up specific game genres, forms of interactions, mode of narratives and understand how they are employed effectively to create a successful game.
4)	Understand game design theories and methods as well as implement them during game development; to make enjoyable, attractive, instructional and immersive according to the target audience.
5)	Understand the technology and computational principles involved in developing games and master the use of game engines.
6)	Understand the process of creation and use of 2D and 3D assets and animation for video games.
7)	Understand and master the theories and methodologies of understanding and measuring player experience and utilize them during game development process.
8)	Comprehend and master how ideas, concepts and topics are conveyed via games followed by the utilization of these aspects during the development process.
9)	Manage the game design and development process employing complete documentation; following the full game production pipeline via documentation.
10)	Understand and employ the structure and work modes of game development teams; comprehend the responsibilities of team members and collaborations between them while utilizing this knowledge in practice.
11)	Understand the process of game publishing within industry standards besides development and utilize this knowledge practice.
12)	Pitching a video game to developers, publishers, and players; mastering the art of effectively communicating and marketing the features and commercial potential of new ideas, concepts or games.