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Course Description

Data modeling has become a pervasive need in today’s business environment. Often the volume of data you need to process goes beyond the capabilities of spreadsheet modeling. When this is the case, the statistical programming language R offers a powerful alternative. With R, you can avoid the cost of standalone statistical packages. Likewise, you don’t need a huge investment in learning the structures required to use a more fully featured programming language.

In this course, you will work through the basic methods of predictive analytics, including generating descriptives, visualization, single and multiple regression, and logistic regression. The benefits of using R for logistic regression are significant, and these are explored in detail. When you have completed this course, you will have gained experience developing R code to solve novel problems in which basic predictive methods are required.

Faculty Author

Chris Anderson

Benefits to the Learner

  • Bring data into working memory within an R integrated development environment (IDE)
  • Create and manipulate basic data structures
  • Generate statistical descriptives and visualizations of a dataset using R
  • Use regression to quantify relationships between variables
  • Quantify relationships between variables when the dependent variable is categorical

Target Audience

  • Analysts
  • Developers
  • Data scientists
  • Functional managers
  • Consultants
  • Any professional that uses data to make business decisions

Accrediting Associations

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
3 week
Dates
Jun 05, 2024 to Jun 25, 2024
Total Number of Hours
24.0
Course Fee(s)
Standard Price $1,380.00
Type
3 week
Dates
Aug 14, 2024 to Sep 03, 2024
Total Number of Hours
24.0
Course Fee(s)
Standard Price $1,380.00
Type
3 week
Dates
Oct 23, 2024 to Nov 12, 2024
Total Number of Hours
24.0
Course Fee(s)
Standard Price $1,380.00
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