AI, Machine Learning, and the Built Environment

Fundamentals & Proptech Applications

A non-technical introduction to Artificial Intelligence (AI) and Machine Learning.

Artificial Intelligence (AI) and its Machine Learning (ML) applications power some of the world’s biggest companies. A key part of Real Estate Technology (Proptech), they power the features of some of the most invested-in, and fastest-growing companies in real estate. However, they have yet to change the day-to-day work of most real estate firms and professionals and remain an untapped opportunity to those able to adapt them to their biggest real estate problems.

This program will constitute a non-technical introduction to AI and Machine Learning, with particular emphasis on their current applications in the fields of Real Estate, Architecture, Landscape, and Urbanism. The main focus of the program will be to give you a high-level overview of what AI & ML are, and what types of problems they are particularly suited to solve.

What to Expect

Woman speaking at a group presentation in front of a co-working space diagram
lively group discussion

We will present the foundational topic of data, including types, acquisition, parsing and their relation to the training of neural networks, as well as more advanced themes such as biases and ethics.

This three-day program will be preceded by short readings, and consist of lectures, hands-on conceptual exercises and group discussions focused on current practical applications of AI & ML in the built environment. Past iterations have looked at the applications of machine learning on property valuation, floorplan generation, recommendation engines, and listing process automation, as used by the world’s most prominent proptech companies, such as Airbnb, Zillow, and Redfin. Given the rate of iteration of AI & ML, each session looks at the most up-to-date examples shaping the industry – from algorithm-powered revenue management systems to “iBuying” applications, and the disruptive potential of large language models (LLMs) such as ChatGPT.

By the end of the program, you will understand what applications of AI & ML offer your practice a potential competitive advantage, and what procedures need to be put in place to ensure successful AI & ML project implementation. Finally, you will gain the background skills necessary to lead a technical team in a machine learning project of your own.

  • Explore the current state of Artificial Intelligence and Machine Learning (ML), with particular emphasis on their applications in the fields of Architecture, Landscape, Urbanism and Real Estate, especially in Proptech.
  • Learn the five rules about which types of problems Artificial Intelligence and Machine Learning are the right answer for tackling.
  • Understand the importance of data acquisition and parsing for machine learning training, as well as identify potential issues of bias and its ethical implications.
  • Acquire the skills to manage a team in a successful machine learning project, without needing the expertise to understand the details of its technical implementation.
  • Build your own organizational guide on the steps you can take immediately to ensure successful future implementations of Artificial Intelligence and Machine Learning in your projects.
  • Gain an understanding of Artificial Intelligence and Machine Learning that allows you to better assess and compare real estate products and services powered by algorithms.
  • Real estate professionals and investors of all types, architects, designers, planners, and proptech professionals.
  • This is a non-technical introduction to AI and Machine Learning. This program is not designed for individuals with an advanced understanding of these topics.


Headshot of Jose Luis Garcia del-Castillo y Lopez

Dr. Jose Luis Garcia del Castillo y Lopez

Lecturer in Architectural Technology Graduate School of Design

Jose Luis Answers Your Questions on AI

Recent Applications of AI/Machine Learning in Real Estate

Redfin Shuts Home-Flipping Business, Lays Off 13% of Staff in Slumping Housing Market

How a Secret Rent Algorithm Pushes Rents Higher

Participant Stories

Headshot of Steve Tatham

Steve Tatham

Theme Park Designer

Sonya Simmonds

Interior Architect and Workplace Strategist

A.I., Machine Learning, and the Built Environment

January 10, 12, & 17, 2024 | 11:00am – 1:00pm Eastern

Tuition:  $1,550
AMDP Elective Units: 1

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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.

Full Discount and Cancellation Policies