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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Graduate School
  2. Department of Fine Arts Education
  3. PhD in Art S Education
  4. PhD in Arts and Crafts Education
  5. Course Structure Diagram with Credits
  6. Practice Based Artificial Intelligence in Art and Design
  7. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 10/06/2026

Code - Course Title Course Type Laboratory + Practice ECTS
RSÖ642 - Practice Based Artificial Intelligence in Art and Design II. SEMESTER 3 +0 7.5
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. SUZAN DUYGU ERİŞTİ
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended
Recommended Resources Bedir Erişti, S. D. (2024). Görsel iletişimde yapay zekâ ve yapay zekâ sanatı. S. D. Bedir Erişti (Ed.), Yeni Medya ve Görsel İletişim Tasarımı içinde (ss. 199-232). Ankara: Pegem Akademi.Gunkel, D. J. (2023). A moral and legal ontology for the 21st century and beyond. The MIT Press. https://doi.org/10.7551/mitpress/14983.001.0001Khandogin, R. (2023). Digital and postdigital art: From aesthetics of a subject to the ontology of an object. Management and Administrative Professional Review, 14(10), 18949-18962.Manovich, L. (2018). AI aesthetics. Moscow: Strelka Press.
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Post-Digital Aesthetics and Art: Historical and Technological Background
Week - 2 Posthumanism and the Transformation of the Creative Subject
Week - 3 Algorithmic Aesthetics and Design
Week - 4 The Nature of Symbiotic Production and Creative Strategies
Week - 5 Advanced Prompt Engineering: Creative Prompting, Creative Coding, and Generative Visual Data
Week - 6 Synthetic Visual Culture: Hybrid Creativity and Aesthetics
Week - 7 Algorithmic Bias and Digital Justice
Week - 8 Midterm Review: Conceptualizing Art Projects Based on Drafts
Week - 9 Explainable AI (XAI): Artistic Transparency and Ethical Production
Week - 10 Creative Workflow Strategies and Participation Design
Week - 11 Interactive Art and Possibilities of Participatory Pedagogy: Public Pedagogy
Week - 12 Implementation Process of Collective Creativity-Oriented Conceptual Projects
Week - 13 Project Prototyping and Feedback Loops
Week - 14 Exhibition, Discussion, and Structuring Public Space Interaction Strategies

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
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