Machine Learning for Sustainable Systems
Building on core material in 6.C01 , emphasizes the design and operation of sustainable systems. Illustrates how 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 urban mobility, energy and water resources, environmental monitoring, infrastructure sensing and control, climate adaptation, and disaster resilience. Projects focus on using machine learning to identify new insights or decisions that can 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.C01 .
Prerequisites & course information
Same subject as 11.C01J Subject meets with 1.C51[J] , 11.C51J Prereq: 6.C01 and (( 1.000 and 1.010 ) or permission of instructor) U (Spring; second half of term) 1-1-4 units
Sources
- Course catalogue ↗2026–2027