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

Digital Artistry & AI: Shaping Visual Intelligence

This course investigates the concept of “Visual Intelligence”—how we interpret images and how machines are trained to do the same. Students will explore the intersection of traditional digital artistry (composition, color theory, anatomy) and computer vision. The curriculum focuses on training the artist’s eye to understand how AI models “see” (pattern recognition, latent space), enabling students to manipulate these systems to produce highly sophisticated, intentional artwork rather than random generations.

§ 01 By the end you can
  1. Analyze the differences between human visual perception and machine computer vision
  2. Apply advanced color theory and composition rules to AI generation workflows
  3. Manipulate "Latent Space" to control artistic output with precision
  4. Critique the aesthetics of machine-generated imagery through an art-historical lens
  5. Create a portfolio that demonstrates a mastery of both digital painting and AI synthesis
§ 02 Sixteen sessions

The whole semester.

  1. 01Visual Intelligence: Human vs. Machine
  2. 02The Anatomy of Style: Deconstructing Art
  3. 03Digital Painting Fundamentals for AI
  4. 04How AI "Sees": Pattern Recognition
  5. 05Latent Space & Vector Mathematics
  6. 06Color Theory in the Age of Algorithms
  7. 07Aesthetics of the "Uncanny Valley"
  8. 08 · MidtermMidterm Examination
  9. 09Advanced Composition in AI
  10. 10Controlling Lighting & Atmosphere
  11. 11Inpainting: The Digital Surgeon
  12. 12Outpainting: Expanding the Canvas
  13. 13Upscaling & Detail Refinement
  14. 14Post-Processing: The Human Touch
  15. 15Developing a Signature Style
  16. 16Final Project: The Synthetic Masterpiece

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 Synthetic Masterpiece

How it’s judged

Recommended reading
  1. Visual Intelligence: Sharpen Your Perception, Change Your Life by Amy E. Herman
  2. The Gage of the Machine (Theoretical papers on Computer Vision)
  3. Color and Light: A Guide for the Realist Painter by James Gurney
  4. Vision and Art: The Biology of Seeing by Margaret Livingstone
  5. Deep Learning with Python by François Chollet (Chapters on Computer Vision)
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