Machine Learning for Sustainable Systems

1-1-4 units · Graduate

Building on core material in 6.C51 , emphasizes the design and operation of sustainable systems. Students learn to leverage heterogeneous data from urban services, cities, and the environment, and apply machine learning methods to evaluate and/or improve sustainability solutions. Provides case studies from various domains, such as transportation and mobility, energy and water resources, environment monitoring, infrastructure sensing and control, climate adaptation, and disaster resilience. Projects focus on using machine learning to identify new insights or decisions to help engineer sustainability in societal-scale systems. Students taking graduate version complete additional assignments. Students cannot receive credit without completion of the core subject 6.C51 .