AI, Machine Learning, and the Built Environment: Fundamentals & Proptech Applications
A non-technical introduction to Artificial Intelligence (AI) and Machine Learning that challenges participants to immediately apply their learnings and develop their own AI innovations with peers.
Artificial Intelligence (AI) and its Machine Learning (ML) applications power the innovations of the world’s biggest companies. However, despite the hype around recent breakthroughs, AI has yet to change the day-to-day work of most real estate firms and professionals and remains an untapped opportunity for industry professionals.
This program will constitute a non-technical introduction to AI and ML, with a particular emphasis on their applications in the fields of Real Estate, Architecture, Landscape, and Urbanism. The program begins with a high-level overview of what AI & ML are and what types of problems they are particularly suited to solve, before challenging participants to develop, with peers, a novel application of machine learning.
This program is a small, cohort-based experience where participants learn live alongside fellow professionals from around the world.
What to Expect
Instructor

Dr. Jose Luis Garcia del Castillo y Lopez
Teaching Professor in Computational Design, Northeastern University
Jose Luis Answers Your Questions on AI
What They Say
The live, small-cohort format fostered meaningful discussions and collaborations.
Participant Stories

Steve Tatham
Theme Park Designer

Sonya Simmonds
Interior Architect and Workplace Strategist

Bo Westerlinck
Senior Design Architect
Registration is open
A.I., Machine Learning, and the Built Environment: Fundamentals & Proptech Applications
March 2, 4, & 6 | 11:00am – 1:00pm Eastern
Online
Tuition: $1,450 (through January 15), $1,650
CEUs: 6 AIA LUs (HSW), 6 AICP/CM, 6 LA/CES (HSW)
AMDP Elective Units: 1
Program size is limited and early registration is recommended.
Discounts & Deadlines
Please email us at [email protected] with any questions and to ask about group signup.
Registration Deadline: 3 hours before the start of the program.
				

