R Course Finder
Showing 131–140 of 166 results
R: Complete Data Analysis Solutions$200.00
Learn by doing – solve real-world data analysis problems using the most popular R packages
Regression and Time Series Analysis$20.00
Identify the most important predictive variables in a model
Regression Machine Learning with R$40.00
Learn regression machine learning from basic to expert level through a practical course with R statistical software.
Regression, Data Mining, Text Mining, Forecasting using R$50.00
Learn Regression Techniques, Data Mining, Forecasting, Text Mining using R
Reporting with R Markdown$25.00
Learn how to write a data report quickly and effectively with the R Markdown package, and share your results with your friends, colleagues or the rest of the world.
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them.
RStudio: Get Started$30.00
his course will teach you to use the R programming language with the RStudio development environment to process data, perform statistical analysis, and create stunning graphical visualizations.
Social Media Analytics with R$20.00
Acquire Social Media from Twitter, Google+ and Facebook, transform, analyzer and produce insights
Spatial Analysis Techniques in R$589.00
The R environment provides a consistent and stable platform for spatial statistical analysis and is the computing environment of choice for most researchers in the field.
Spatial data analysis with R$280.00
As spatial datasets get larger more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for working with spatial data thanks to its powerful analysis and visualisation packages. This course introduces the basics of how R can be used for spatial data. No previous experience of computer programming is required but participants would benefit from some experience of GIS and spatial data formats and concepts.