R Programming Course

To be a well-rounded data scientist, it is imperative to know the ins and outs of both Python and R, the latter of which we will discuss in this course. In addition to all the primary coding functionality, we will learn more about what makes R unique, diving into how R leverages vectors and matrices to read in and work with data.

Additionally, we will discuss the mechanics of the powerful dplyr library, which allows extreme ease in manipulating datasets. We will then discuss data visualization, highlighting the advantages of the highly customizable ggplot2 library, which powers some of the most intricate graphs seen in data journalism and research today.

Finally, we will go through basic statistics and discuss the statistical tools within R, such as constructing confidence intervals, hypothesis testing, and ANOVA testing.

Course Curriculum

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Module 1: R Fundamentals

Module 2: Working with Data:Dplyr

Module 3: Data Visualization in R

Module 4: Statistics

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