Engineering Computation and Data Science

3-2-7 units · Graduate

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 will complete additional assignments and project work. Programming experience in a language is required.