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Computational Design introduces the principles of algorithmic thinking and parametric modeling through Grasshopper. The course teaches students to create, manage, and optimise complex geometries using data-driven design methods. By learning to build and navigate parametric systems, students gain the ability to make informed, performance-based design decisions and explore generative workflows that expand creative and technical possibilities in architecture and design.
Syllabus
Credits: Minimal Surface, Complex Forming Seminar, MAA01 2019/20
Computational design lies at the core of innovation in architecture and design nowadays. Increasingly the tools that we now use to design have expanded the range of our options to design, allowing for performance and complexity, and extending beyond the three dimensional space into a virtually limitless parametric realm of different versions of the design intent upon which to choose from.
By being able to effectively set up a parametric model, navigate these options and confronting them with analytical tools that are embedded in the design process, designers are able to take better informed decisions in order to create projects that are complex and performative by whichever metrics the designer wishes to challenge them with.
For this purpose, Grasshopper has significantly become the standard for computational design, not only within academia but across many trades and disciplines that encompass the creating process, providing easy access to algorithmic thinking and a large ecosystem of plugins that provide easy access to a broad range of tools for advanced design.
This course focuses on teaching the fundamentals of visual scripting through Grasshopper while exploring the most basic concepts of computational design. From the generation of geometry as data into how to manage multiple geometrical information algorithmically, students will become proficient in algorithmic thinking in order to navigate fluently in the complexity of geometrical data.
Learning Objectives
- Understand the fundamental concepts of computational design
- Develop strategies for building algorithms
- Gain knowledge of the basic principles of generative design
- Be able to generate parameterized processes
- Apply data-driven design logics
- Learn how to create dynamic models
- Acquire deeper knowledge of algorithmic design concepts and geometry parameterization
- Gain advanced understanding of data management in Grasshopper
- Learn in depth about the parameterization of complex geometries
- Explore the most recent workflows for complex modeling
- Understand the concepts and practical applications of optimization algorithms
Faculty
Projects from this course
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