This course explores the integration of Stable Diffusion with parametric architectural design workflows. You will begin by learning how to set up Stable Diffusion using RunPod for cloud-based AI rendering and how to work with custom models efficiently.

The course then dives into complete Stable Diffusion workflows tailored for architects and designers. You will explore text-to-image, image-to-image translation, and AI rendering techniques that transform parametric geometry into high-quality architectural visuals.

A strong focus is placed on ControlNet, particularly the Canny model, to render parametric facades, towers, and complex forms while maintaining structural accuracy. You will also learn how to generate AI-based architectural plans using parametric masks and style-driven plan generation techniques.

Additionally, the course demonstrates how to integrate AI directly into Rhino and Grasshopper environments, enabling real-time generative design exploration. Topics such as AI texture creation, landscape generation, and diffusion-based facade rendering are covered in practical examples.

By the end of this course, you will understand how to combine parametric modeling with AI image generation to accelerate architectural visualization, concept development, and creative exploration.