The Master of Science in Computational Design Practices (M.S.CDP) is an innovative program for recent graduates and practitioners that extends and integrates disciplines between architecture, data visualization, and urban planning—focusing specifically on computational design practices for the built environment at multiple scales. It aims to pioneer new concepts and pedagogies for an integrated multi-scalar and spatial approach to computational design at Columbia GSAPP. The M.S.CDP curriculum encourages critical and creative engagement with spatial computational design as both method and practice.
The M.S.CDP program was launched in 2021 for pre- and post-professional students and encourages applications from a range of backgrounds. The program is oriented toward the training of future design practitioners and aims to expand the discipline’s range of intellectual entanglements and cultivate new paradigms for scholarly research, experimental practice, creative technology, communication, and action. We take it as a given that from the scale of the project to that of the planet, the uses of computational design methods, and tools are most successful when their limits and their contexts—technical, social, political, aesthetic, and ethical—are confronted and surpassed to allow equitable ways of imagining, creating and coding space. The tools, data, and technology we deploy in the design process are never neutral. Faculty in the sequence take on discrete parts of this array—data visualization, sensors and data analysis, simulation, optimization, sensing, procedural modeling, rendering, interface design, Geographic Information Systems (GIS), Building Information Management (BIM)—and expose students to technical, critical, and creative ways to transform and develop their processes of design.
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Each student is asked to clarify an independent research problem over three semesters, culminating in a forward-looking capstone project for the final Design in Action colloquium. Three colloquium courses—Methods as Practices, Practices as Methods; Explore, Explain, Propose; and Design in Action—provide a critical, productive, and supportive structure for students to develop a clear position and methodology for their work, as well as a plan for its implementation. Students participate in the field discursively as well—reading and writing about current debates as well as historical approaches to technology and the built environment. They are guided through creative and iterative design processes as well as methods-oriented workshops to facilitate their work and capstone projects. Foundation courses are intended to provide a set of seven core competencies for students in computational design methods in architecture and planning. Three of these foundation courses are available exclusively online to students before the start of the program, as well as to learners everywhere: Computational Drawing, Mapping and Data, and Programming for Design Practices. Other foundation courses include Computational Modeling, Computational Design Workflows, Responsive Architecture, and Design Intelligence. The program also offers nearly 36 existing advanced elective courses across the School, enabling students to explore and cultivate their particular direction and approach to research.
A part-time option allows students to complete the curriculum over the course of three years.