Machine Learning for Molecular Engineering
Building on core material in 6.C51 , provides an introduction to the use of machine learning to solve problems arising in the science and engineering of biology, chemistry, and materials. Equips students to design and implement machine learning approaches to challenges such as analysis of omics (genomics, transcriptomics, proteomics, etc.), microscopy, spectroscopy, or crystallography data and design of new molecules and materials such as drugs, catalysts, polymer, alloys, ceramics, and proteins. Students taking graduate version complete additional assignments. Students cannot receive credit without completion of the core subject 6.C51 .
Prerequisites & course information
Same subject as 10.C51[J] , 20.C51[J] Subject meets with 3.C01[J] , 7.C01 , 7.C51 , 10.C01[J] , 20.C01[J] Prereq: Calculus II (GIR) , 6.100A , and 6.C51 G (Spring) 2-0-4 units
Sources
- Course catalogue ↗2026–2027