ENGR 014. Data Analytics for Engineers

This course provides a broad introduction to the principles and methods of data analytics with applications to engineering prblems. Students learn techniques for data preprocessing, cleaning and visualization, as well as dimensionality reduction usinig principal component analysis (PCA), forward and backward stepwise regression, and lasso regression. Basic concepts in probabilty, statistics and hypothosis testing are introduced as needed. The course covers linear and multilinear regression, along with regularization methods such as ridge and lasso regression. Techniques for clustering classification and predictive modeling are also introduced.
Prerequisite: MATH 025 or equivalent or permission of the instructor.
Natural sciences and engineering practicum.
Lab required.
1 credit.
Fall 2026. Piovoso.
Catalog chapter: Engineering
Department website: http://www.swarthmore.edu/engineering

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