Akademik Dersler - Tanıtım

Last Updated: 26/06/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
OGP218 - Generative AI Tools in Game Development	IV. SEMESTER	2 +2	5.0

Language of Instruction	Türkçe
Course Type	Area Elective Courses
Course Instructor(s)	ÖĞR. GÖR. GÜVENÇ USANMAZ
Mode of Delivery	This course is delivered through face-to-face instruction. Theoretical lectures, in-class discussions and laboratory sessions are integrated throughout the semester. Current generative AI tools are used as examples; the instructor may prefer equivalent tools.
Place of Delivery
Used Educational Platforms
Prerequisites	There are no prerequisites or co-requisites for this course.
Courses Recomended	It is recommended to have completed OGP104 Programming II and OGP108 2D Game Development Studio before taking this course. Basic Unity/C# knowledge and game project experience will facilitate the learning process.
Recommended Resources	OpenAI. Prompt Engineering Guide: https://platform.openai.com/docs/guides/prompt-engineeringAnthropic. Prompt Engineering Overview: https://docs.anthropic.com/GitHub Docs. GitHub Copilot: https://docs.github.com/copilotUnity Technologies. Unity AI tools documentation: https://docs.unity3d.com/
Work Placement	This course has no internship or placement requirement.
Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Introduction to generative AI; use cases in the game industry; course scope, timeliness and limitations.
Week - 2		Prompt engineering: context, role, constraints, iteration; prompt patterns for game development.
Week - 3		AI-assisted coding: context-aware generation, game mechanics prototyping; limits and verification.
Week - 4		AI-assisted development environments (AI IDEs): example workflows with Copilot, Cursor, etc.; use with version control.
Week - 5		Visual content generation: concept art, textures, sprites; style consistency and reference management.
Week - 6		Audio content: AI sound effects, music and voice-over; basics of engine integration.
Week - 7		Text and narrative: dialogue, quest text, dynamic narrative drafts; the human editor role.
Week - 8		Procedural content vs generative AI; when rule-based vs when LLM/visual models.
Week - 9		Integration into Unity and game projects: asset pipeline, license tags, metadata and source tracking.
Week - 10		Ethics, copyright and originality: training data, attribution, academic integrity; publisher/platform policies.
Week - 11		Limits and risks: hallucination, bias, privacy; disclosure to players and trust.
Week - 12		Quality control: human-in-the-loop, testing, iteration; what AI does well/poorly.
Week - 13		Case studies: indie and studio workflows; discussion of successful/unsuccessful examples.
Week - 14		End-of-term project presentation; ethics evaluation report; course wrap-up and future trends.

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Assessment Method and Passing Requirements
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