Introduction to Generative Design

  • by Danil
  • Course level: Beginner

Description

This course provides an overview of the generative design methodology, including its theoretical context, its foundations in artificial intelligence, and its applications in industry. Participants will learn how to combine techniques of computational design, simulation, and optimization to develop generative workflows which can explore a wide space of possible designs while revealing the most optimal solutions to a complex set of performance requirements. They will also get an introduction to the tools and technologies used to enable these workflows.

Topics for this course

4 Lessons02h 03m 28s

Introduction to Generative Design

Case Study: Bionic Partition00:30:59
Case Study: Autodesk, Toronto00:26:27
Demo: Generative Design overview00:21:35

About the instructors

Danil Nagy is a designer, developer, and entrepreneur focusing on applications of computational design and automation for the building industries. His expertise includes computational geometry, digital fabrication, simulation, optimization, machine learning, and data visualization. Danil teaches at the Graduate School of Architecture, Planning and Preservation (GSAPP) at Columbia University in New York, where his courses focus on architectural visualization, generative design, and applications of artificial intelligence. Danil was formerly a Principal Research Scientist at Autodesk Research. He is the founder of Colidescope, a consultancy focused on bringing digital transformation tools to the Architecture, Engineering, and Construction (AEC) industries.
4.67 (3 ratings)

16 Courses

132 students

Material Includes

  • Over two hours of on-demand video
  • Downloadable demo files to follow along with video tutorials

Requirements

  • No prior experience is necessary to complete this course