What you'll learn
- 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 State.
- 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.
Course description
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 the practical applications of Machine Learning in the built environment.
By the end of the program, you will have gained a deep understanding on the potential affordances of AI & ML in relation to your practice, and how it may bring you a competitive advantage in the near future. With this program, you will gain the background skills necessary to lead a technical team into the implementation of a ML project of your own, as well as how to prepare yourself for this moment, starting today!
Associated Schools
Harvard Graduate School of Design
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