Linear Algebra for Data Science in R

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This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
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Linear algebra is one of the most important set of tools in applied mathematics and data science. In this course, you’ll learn how to work with vectors and matrices, solve matrix-vector equations, perform eigenvalue/eigenvector analyses and use principal component analysis to do dimension reduction on real-world datasets. All analyses will be performed in R, one of the world’s most-popular programming languages.

Instructor(s)

Eric Eager
DataCamp
via DataCamp
Free Trial Available
English
4 Hours
Self paced