R Course Finder
Find an R course quickly, using the filters on the right.
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Note: Prices shown for all paid courses on DataCamp platform are monthly subscriptions, which give full access to all courses on this platform.
Showing 1–10 of 45 results
In this course you will learn how to program in R and how to use R for effective data analysis
Linear Regression and Modeling$71.00
This course introduces simple and multiple linear regression models
Advanced R Programming$50.00
This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools.
Applied Predictive Analytics$589.00
In this online course, “Applied Predictive Analytics,” you will apply data mining techniques in a real world case study
After taking this online course, “Bayesian Statistics in R” you will be able to install and run rjags, a program for Bayesian analysis within R.
This course describes Bayesian statistics, in which one’s inferences about parameters or hypotheses are updated as evidence accumulates
Biostatistics in R with Clinical Trial Applications$589.00
This online course, “Biostatistics in R: Clinical Trial Applications” covers the implementation in R of statistical procedures important for the clinical trial statistician.
Building Data Visualization Tools$50.00
Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new data types requires the development of new visualization techniques and building blocks. This course provides you with the skills for creating those new visualization building blocks.
Building R Packages$50.00
This course covers the primary means by which R software is organized and distributed to others.
Building R PackagesFree!
This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross-platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN.