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Advanced Computational Design (ABPL90123)
Graduate courseworkPoints: 12.5Not available in 2024
Overview
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This subject focusses on computational tools, processes, and theories for architectural design. The topics covered range from basic scripting for design automation and fabrication to the application of optimisation and machine learning techniques for performative design.
This is not an introductory subject to computational design. It builds on previous knowledge of design thinking and computational design tools, processes, and applications.
Prescribed software programs with a cost
McNeel Rhino
Prescribed software tools
Image editing software
Vector editing software
Layout software
Details of software availability and pricing are captured at: https://msd.unimelb.edu.au/current-students/student-experience/it-support
Intended learning outcomes
Having completed this subject it is expected that the student be able to:
- Familiarise with a variety of computational design techniques, and appreciate both challenges and limits of using such techniques in real-world scenarios;
- Formulate a design problem in computational terms;
- Apply a variety of optimisation and machine learning techniques to solve design problems
- Develop a critical awareness of the relationship between design thinking and design computing
Generic skills
- Proficiency in the use of computational design tools for design automation (scripting), optimisation and machine learning.
- Critical reflection, thinking, and analysis, related to computation design tools, processes and theories.
- Problem-solving applied to computational design.
- Ability to illustrate a computational design process through diagrams, codes and in writing.
Last updated: 19 February 2024