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Linear Algebra for Data Science in R

IntermediateSkill Level
4.7+
51 reviews
Updated 08/2022
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
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RProbability & Statistics4 hr15 videos56 Exercises4,000 XP17,394Statement of Accomplishment

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Course Description

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.

Prerequisites

Introduction to R
1

Introduction to Linear Algebra

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2

Matrix-Vector Equations

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3

Eigenvalues and Eigenvectors

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4

Principal Component Analysis

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Linear Algebra for Data Science in R
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*4.7
from 51 reviews
78%
16%
6%
0%
0%
  • Manousos
    1 day

  • Kimberly
    4 days

  • Joseph
    7 days

  • Richard
    14 days

  • Hengjie
    17 days

  • Marie Sami
    18 days

Manousos

Kimberly

Joseph

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