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DSCI 501 Quantitative Foundations of Data Science 3.0 Credits

Linear algebra, calculus, probability and statistical methods are essential foundation areas required for an effective understanding and application of data science. In this course, students will get a gentle introduction to these important areas of quantitative reasoning. Along with introducing basics of linear algebra, calculus, probability, and statistical methods, this course will also introduce their computational application through the Python programming language. Concepts will be demonstrated using various python packages.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit

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