ENGRD 2720

Data Science for Engineers

Course Description

Course information provided by the 2019-2020 Catalog.

An introduction to data science for engineers. The data science workflow: acquisition and cleansing, exploration and modeling, prediction and decision making, visualization and presentation. Techniques for different steps in the workflow including outlier detection, regression, change-point detection, and classification. An introduction to probability, focusing on Gaussian distributions and linear models. Methods for combining domain-agnostic data analysis tools with the types of domain-specific knowledge that are common in engineering. Programming projects in Python.

Prerequisites/Corequisites Prerequisite: MATH 1920 and either CS 1110 or CS 1112.

When Offered Fall.

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