MATH 227
Credit: 3 hours.
Linear algebra is the main mathematical subject underlying the basic techniques of data science. Provides a practical computer-based introduction to linear algebra, emphasizing its uses in analyzing data, such as linear regression, principal component analysis, and network analysis. Students will also explore some of the strengths and limitations of linear methods. Students will learn how to implement linear algebra methods on a computer, making it possible to apply these techniques to large data sets.
Credit is not given for both Math 227 and any of Math 125, Math 225, Math 257, Math 415, or ASRM 406. Prerequisite: Assumes an introductory knowledge of Python, such as students acquire in STAT 107.
Students must register for one lecture and one lab section.
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