Examine local image-generation workflows, model choices, and responsible review of generated or suspected synthetic images.
Explore how desktop interfaces, model sources, and text-to-image workflows fit together, then consider what can and cannot be inferred from an image. Learners plan safe experiments, track model and prompt provenance, and review output for rights, disclosure, and misleading use. These original activities avoid claiming that a particular interface is current or that image detectors can conclusively identify provenance. Only use models, prompts, and images you are permitted to use.
Map the components and dependencies in a local or hosted image-generation workflow. Record prompt, model, settings, and source information needed to reproduce or review an output. Explain why image detection results are uncertain and define a proportionate human review process.
Familiarity with downloading files and using a desktop application is helpful. No coding is required, and all activities can be completed on paper. Verify current model licenses and tool requirements; do not use another person's likeness, protected material, or deceptive synthetic media without appropriate permission and disclosure.
Learners with basic familiarity who are ready to build practical, independent skills
People who learn best through examples, guided lessons, and hands-on practice
Professionals, creators, and independent builders looking for a repeatable workflow
Lesson 1 is free
4 lessons · Intermediate · Full course.
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