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"Portions of this material are derived from RStudio's ''." Please include a link to the original in your content saying, This course is part of several tracks, including Data Analyst with R, Data Scientist with R, and R Programming, all of which can help you develop your knowledge.RStudio offers several resources to make it easier for you to teach R, ranging from semester-long courses to more intense (but much shorter) workshops.Īll of these materials can be reused and remixed freely under Creative Commons licenses. These sought-after skills can help you progress in your career and set you up for further learning. Finally, you’ll explore how to work with R data frames and lists.īy the time you’ve completed our Introduction to R course, you’ll be able to use R for your own data analysis. You’ll also examine how R uses factors to store categorical data. Next, you’ll learn how to work with matrices in R, learning how to create them, and perform calculations with them. Once you’ve had a chance to practice, you’ll move on to creating vectors and try out your new R skills on a data set based on betting in Las Vegas.
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You’ll get started with basic operations, like using the console as a calculator and understanding basic data types in R. You’ll gain useful coding skills and be ready to start your own data analysis in R. This introduction to R course covers the basics of this open source language, including vectors, factors, lists, and data frames.
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R's ability to handle complex analyses such as machine learning, financial modeling, and more makes it a valuable asset for a wide range of data-related tasks. R programming language is a useful tool for data scientists, analysts, and statisticians, especially those working in academic settings.
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