
| Course Code | : RTS319 |
| Course Type | : Area Elective |
| Couse Group | : First Cycle (Bachelor's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 1 |
| Prt. | : 2 |
| Credit | : 2 |
| Lab | : 0 |
| ECTS | : 5 |
The objective of this course is to provide students with the cinematographic, aesthetic, and technical foundations of AI-driven image and video generation. Throughout the course, students will learn to integrate traditional cinematic language (lighting, composition, lens selection, art direction) with AI algorithms, utilize artificial intelligence as a creative assistant in pre-production processes, and develop innovative storytelling methods in moving image production. Furthermore, by discussing the ethical, copyright, and labor implications of AI in the film industry, the course aims to prepare students as visionary and ethically responsible content creators for the future of the media landscape.
This course covers the fundamental use of AI-backed visual generation tools and the integration of these technologies into creative processes in cinema and television. Throughout the semester, students will explore core application areas such as text-to-image/video generation, AI-driven concept art, visual storyboarding, and digital editing assistance. In addition to technical tools, the adaptation of AI use to cinematographic rules, copyright issues, and ethical debates constitute the core elements of the course. By the end of the semester, students are expected to develop a practical project that combines these tools with traditional filmmaking workflows.
| 1. | Applies traditional cinematic language, including camera angles, shot sizes, lens types, and lighting designs, using accurate prompts in AI visual generation tools. |
| 2. | Analyzes character and setting consistency required for cinematic narrative using advanced parameters of AI tools and maintains visual continuity across scenes. |
| 3. | Integrates AI-generated static images, videos, audio, music, and editing elements to create a cohesive cinematic workflow. |
| 4. | Critically discusses and evaluates ethical issues brought by AI usage in the cinema and media industries, such as copyrights, actor rights, deepfakes, and manipulation. |
| 5. | Designs an original short cinematic project with narrative value, utilizing AI tools as a creative assistant from the concept stage through to the final edit. |
| 1. | https://nofilmschool.com/the-real-ai-revolution-in-filmmaking-is-happening-behind-the-scenes |
| 2. | Runway. (t.y.). Runway academy: Learning generative video and AI tools. Erişme tarihi: 26 Mayıs 2026, https://learn.runwayml.com/ |
| 3. | Midjourney. (t.y.). Midjourney documentation: Prompts, parameters, and cinematic styling. Erişme tarihi: 26 Mayıs 2026, https://docs.midjourney.com/ |
| 4. | Curious Refuge. (t.y.). AI filmmaking: The ultimate guide to creating films with artificial intelligence. Erişme tarihi: 26 Mayıs 2026, https://curiousrefuge.com/ |
| Type of Assessment | Count | Percent |
|---|---|---|
| Attending Lectures | 5 | %5 |
| Assignment | 3 | %15 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 1 | 14 |
| Lecture - Practice | 14 | 0 | 2 | 28 |
| Assignment | 4 | 5 | 5 | 40 |
| Midterm Examination | 1 | 10 | 1 | 11 |
| Final Examination | 1 | 30 | 1 | 31 |
| TOTAL WORKLOAD (hours) | 124 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | PÇ-12 | PÇ-13 | PÇ-14 | PÇ-15 | PÇ-16 | |
OÇ-1 | 4 | 3 | 5 | 5 | ||||||||||||
OÇ-2 | 3 | 4 | 4 | 5 | 5 | |||||||||||
OÇ-3 | 5 | 5 | 4 | 3 | 3 | 5 | ||||||||||
OÇ-4 | 5 | 5 | 5 | |||||||||||||
OÇ-5 | 5 | 4 | 5 | 5 | 4 | 5 | 4 | 5 | 5 | |||||||