A.I., Machine Learning, and the Built Environment: Fundamentals & Proptech Applications
$1,250 (until Jan 31), $1,450
Submitted for AIA CE credit
This is a sponsored event by the Harvard Graduate School of Design Executive Education.
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. 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.