Course Syllabus

Sequence: 

Columbia GSAPP Building TECH and Visual Studies

 

Course Name and Semester 

Example: Fall 2023 A4815 X Information Modeling

 

Room Number

Ware Lounge

 

Your CU Email Address

yz2311@columbia.edu

 

General Course Description

 

Data is the language of cities. This data is inherently spatial. Designers and planners are uniquely suited to leverage it for informed decision making. Accordingly, this course introduces students to computational design through a unique data-driven workflow using Rhino, Grasshopper, and other platforms for visual exploration of design and data. 

 

Building Information Modeling has become pervasive throughout the design industry. This class expands the imagination and scope of the model to include geo-spatial data at multiple scales -- cities, neighborhoods, and buildings -- to capture the nuances of urban dwelling. Through a combination of technical bootcamps, readings, and projects, students will develop technical skills alongside a critical understanding of computational design. 

 

Topics Covered

Building Performance Evaluation Tools 

• Custom Spatial Tool Building
• Origin / Destination travel demand modeling
• Environmental simulation, physics, and validating proxies
• Performance-based zoning and policy

 

Analysis, Visualization and Communication   

• Advanced techniques in rhino and grasshopper
• Statistical techniques for analyzing design spaces
• Using web based visual interfaces for design space exploration

 

Creating Computational Design Models 

• Building iterative architectural and urban scale procedural models
• Defining inputs, linking procedural models to performance tools 
• Running out design spaces
• Theory and history around computational design

 

Urban Data Exploration, Analysis and Speculation 

• Data exploration: charts, maps, visualization 
• Thinking critically about biases in data and computation

 

The techniques introduced in this course are applicable across architectural and urban scales; at its core, this class is about creating tools to measure performance, drawing with data, and visualization for decision making. However, the projects will focus on the urban scale and develop new spatial metrics, data visualization, performative zoning/policies, and data-driven building types. Projects must be spatial, speculative, iteratively tested, and quantitatively evaluated.

 

This course will be structured as a flipped classroom. With a few exceptions, technical content will be taught through video tutorials outside of class. Class time will be for reviews, reading discussions, and in-class workshops. Help sessions will be provided out of class to help with the technical content as needed. Students must be proficient in Rhino. Grasshopper proficiency is not required, but a basic understanding will help. For a quick overview, refer to  Intro Grasshopper tutorial sequence (1-3).

 

Grading will be 30% attendance + class participation, 40% weekly assignments, and 30% for the final project.