Course information
All the information you need.
If you have further questions, have a need you’d like to share, or just want to know more about this course, please email courses@problemlibrary.org
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Course instructor: Danny Jones
Course 1: Generative Design — Creating Your Own Dataset
Rapidly craft a personal, stylistically unified dataset using generative design techniques in Figma (creating scalable systems, color palettes, and modular layouts) and Cinema 4D (generating dynamic 3D forms, iterative lighting setups, and procedural compositions).
I’ll introduce fundamental generative principles—such as controlled variation, systematic experimentation, and iterative workflows—to establish a strong visual foundation that enhances your AI-driven creative process.
- Goal: Quickly build a high-quality, stylistically consistent dataset.
- Duration: 1 session (3–4 hours)
- Tools: Figma, Cinema 4D, optional photography, illustration
- Topics:
- Essentials of a strong dataset: consistency, variation, intention
- Moodboarding and aesthetic direction
- Rapid prototyping: type systems, color palettes, 3D forms, and spatial layouts
- Deliverables:
- Curated mini-dataset (20–50 images)
- Initial visual series demonstrating a clear aesthetic direction
- Outcome: Ready-to-use dataset for AI model training.
Course 2: Model Building — Training and Remixing Your Aesthetic
Turn your curated dataset into a personalized, AI-powered creative engine by fine-tuning off-the-shelf AI models. We’ll cover the essentials of dataset curation (tagging, naming, and organizing visual assets), model training workflows (using tools like Runway ML, Krea, or Google Colab), and prompt engineering (crafting effective language prompts to steer your model precisely). You’ll quickly learn how to iteratively test and refine your outputs, ensuring the AI-generated visuals authentically reflect your distinct creative voice.
- Goal: Train or fine-tune an AI model using accessible platforms.
- Duration: 1 session (3–4 hours)
- Tools: Runway ML, Krea, Replicate, ComfyUI, Google Colab
- Topics:
- Quick intro to AI models: diffusion, LoRAs, fine-tuning, prompting
- Dataset tagging, naming, and metadata
- Streamlined training workflows
- Prompt engineering essentials
- Deliverables:
- Personalized AI model or prompt-based output system
- Initial AI-generated artworks
- Outcome: Customized AI tool reflecting students’ creative voice.
Course 3: Art Showcase — Sharing the Output
Curate your AI-generated art into a cohesive and compelling series, ready to be showcased publicly at an IRL exhibition hosted at Problem Library. Each student will have a dedicated spotlight to share their unique creative process—from showcasing their original curated datasets and revealing the behind-the-scenes workflows, to presenting their final generative artworks. You’ll have the opportunity to confidently discuss your artistic journey, demonstrate the intentionality behind your generative designs, and celebrate your distinct creative voice alongside peers, friends, and the broader creative community.
- Goal: Rapidly curate and exhibit artwork publicly.
- Duration: 1 session (3–4 hours) + public event
- Format:
- Select 3 final artworks
- Optional process artifacts (datasets, prompts, notes)
- Efficient exhibition setup
- Community event (IRL, digital, or hybrid)
- Bonus Features:
- Printed group zine
- Interactive prompt stations
- Optional brief artist talks or discussions
- Outcome: Publicly presented work, defined creative process, community exposure.
Additional Opportunities
- Guest critiques by AI artists or designers
- Private Discord or Slack for peer collaboration
- Opportunities for ongoing mentorship or group projects
Pricing
- Sliding Scale: $350–$600 (early-career or independent artists)
- Standard: $650–$900 (group critiques, zine included)
- Premium: $1200–$1500 (personalized feedback, extensive support)
Early Bird rates: 25% discounted tickets available starting April 25th
Stuff to Bring to Class
- Laptop (charger included!)
- Figma Account (free account is fine)
- Cinema 4D (trial or licensed—optional but recommended)
- Basic understanding of design principles (color, typography, layout)
- KREA account (for AI model training)
- Notebook and pen (for quick notes and sketches)
- Personal inspirations (moodboard references, images, artists you admire)