A.I., Machine Learning, and the Built Environment | Harvard University

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 worlds 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.

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.