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AI & Digital Arts · MS elective · 3 credit hours · 16 sessions

Digital Art and Artificial Intelligence

This studio-based course bridges the gap between traditional digital artistry and cutting-edge artificial intelligence. Students will explore how AI tools can augment human creativity rather than replace it, focusing on hybrid workflows that combine manual digital painting, photo-bashing, and neural rendering. The course emphasizes style transfer, image synthesis, and the ethical integration of AI into professional artistic pipelines.

§ 01 By the end you can
  1. Master the integration of AI generation tools within traditional software (e.g., Photoshop, Blender)
  2. Apply neural style transfer and image-to-image techniques to refine artistic concepts
  3. Develop consistent character and environment designs using AI-assisted workflows
  4. Critically analyze the ethical and legal implications of AI in digital art
  5. Produce a high-quality digital art portfolio demonstrating hybrid human-AI creativity
§ 02 Sixteen sessions

The whole semester.

  1. 01Introduction to Digital Art & AI Ecosystems
  2. 02Digital Painting Fundamentals Refresher
  3. 03Introduction to Stable Diffusion & Midjourney
  4. 04Prompt Engineering for Artistic Control
  5. 05Image-to-Image & Inpainting Techniques
  6. 06Composition & Storyboarding with AI
  7. 07Photobashing: Merging Assets with AI
  8. 08 · MidtermMidterm Examination
  9. 09Character Design: AI Consistency Workflows
  10. 10Environment Art & Neural Landscapes
  11. 11Texturing & Material Generation with AI
  12. 123D Paint Over & AI Projection Mapping
  13. 13Upscaling & Detail Refinement
  14. 14Style Training (LoRA/Dreambooth concepts)
  15. 15Final Project: The Hybrid Masterpiece
  16. 16Final Project Submission & Critique

Midterm around session 8. Final project briefed at session 8 or 9 and developed in stages until the juries.

§ 03 Final project

Final Project: The Hybrid Masterpiece

How it’s judged

Recommended reading
  1. The Artist’s Guide to AI: Creative Workflows for Midjourney and Stable Diffusion by S. K. Taji
  2. Generative Deep Learning by David Foster
  3. Digital Painting Techniques by 3dtotal Publishing (for foundational skills)
  4. AI Art: Machine Learning, Painting, Mirrors by Joanna Zylinska
  5. Steal Like an Artist by Austin Kleon (for conceptual framing)
From the PGA Journal
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