• Focuses on in-depth modeling of engineering tasks as machine learning problems. Emphasizes framing, method design, and interpretation of results. In comparison to broader prerequisite 6.C01, this project-oriented subject consists of deep dives into select technical areas or engineering tasks involving both supervised and exploratory uses of machine learning. Explores technical areas such robustness, interpretability, fairness and engineering tasks such as recommender systems, performance optimization, and automated design. Students taking graduate version complete additional assignments. Students cannot receive credit without completion of the core subject 6.C01. Enrollment may be limited.

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