Description: There is a wide variety of support libraries in R to help you perform tasks such as rendering, documentation, referencing, string manipulation, and library management. In this course, you'll explore a range of domain-specific tools in R.
Target Audience: Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science
Duration: 01:09
Description: There are a variety of frequently used programming techniques you can apply to get the most out of the R language. This course covers a variety of techniques in R in order to increase the quality and performance of your R programs.
Target Audience: Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science
Duration: 01:32
Description: One of the most important tasks in any programming language or development environment is debugging. In this course, you'll discover ways you can debug R code and improve the resilience of your R programs through defensive programming.
Target Audience: Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science
Duration: 00:56
Description: To carry out data science, you need to gather, filter, transform, and explore data sets. In this course, you'll explore examples of data wrangling in R.
Target Audience: Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science
Duration: 01:27