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Spring 2019 Semester
Feb 23, 2019
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Information Select the desired Level or Schedule Type to find available classes for the course.

CS 2810 - Mathematics of Data Models
Studies the methods and ideas in linear algebra, multivariable calculus, and statistics that are most relevant for the practicing computer scientist doing machine learning, modeling, or hypothesis testing with data. Covers least squares regression, finding eigenvalues to predict a linear system’s behavior, performing gradient descent to fit a model to data, and performing t-tests and chi-square tests to determine whether differences between populations are significant. Includes applications to popular machine-learning methods, including Bayesian models and neural networks.
4.000 Credit hours
4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
NUpath Analyzing/Using Data, NUpath Formal/Quant Reasoning, Computer&Info Sci

Restrictions:
Must be enrolled in one of the following Levels:     
      Undergraduate

Prerequisites:
Undergraduate level CS 1800 Minimum Grade of D- and Undergraduate level CS 2500 Minimum Grade of D-

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