Engineering Computation and Data Science
Description
Presents engineering problems in a computational setting with emphasis on data science and problem abstraction. Covers exploratory data analysis and visualization, filtering, regression. Building basic machine learning models (classifiers, decision trees, clustering) for smart city applications. Labs and programming projects focused on analytics problems faced by cities, infrastructure, and environment. Students taking graduate version complete additional assignments and project work. Subject meets with 1.001 Prereq: Calculus I (GIR) and (( 6.100A and 6.100B ) or ( 6.100L and 16.C20[J] )) U (Spring) 3-2-7 units. REST
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1.00 has possible credit equivalents including 06SM240M001 at University of Zurich.