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MS&E 226. "Small" Data. 3 Units.

This course is about understanding "small data": these are datasets that allow interaction, visualization, exploration, and analysis on a local machine. The material provides an introduction to applied data analysis, with an emphasis on providing a conceptual framework for thinking about data from both statistical and machine learning perspectives. Topics will be drawn from the following list, depending on time constraints and class interest: approaches to data analysis: statistics (frequentist, Bayesian) and machine learning; binary classification; regression; bootstrapping; causal inference and experimental design; multiple hypothesis testing. Class lectures will be supplemented by data-driven problem sets and a project. Prerequisites: CME 100 or MATH 51; 120, 220 or STATS 116; experience with R at the level of CME/STATS 195 or equivalent.

School of Engineering

http://exploredegrees.stanford.edu/schoolofengineering/

...Probability, MS&E 120 Probabilistic Analysis , MS&E...182, CEE 183, CEE 226, CEE 241, OR...

Civil and Environmental Engineering

http://exploredegrees.stanford.edu/schoolofengineering/civilandenvironmentalengineering/

...Energy (SDC-E) SDC-Structures...Environmental Engineering MS program may...CEE , CEE 226 Life Cycle...