![]() ![]() As of August 2020, R is the 8th most popular programming language (its highest position ever - in 2019, for example, it was the 20th most popular), ahead of SQL, MATLAB, and Swift (Python is third most popular, after C and Java). According to TIOBE, a software QA automation company that ranks programming languages based on how often they’re searched for online, R is catching up with Python, fast. ![]() ![]() The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.The programming language R continues to gain popularity. We help you develop a skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. Rather than covering every R skill you might need, you’ll build a strong foundation to prepare you for the more in-depth courses later in the series, where we cover concepts like probability, inference, regression, and machine learning. You’ll learn how to apply general programming features like “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data. We’ll cover R's functions and data types, then tackle how to operate on vectors and when to use advanced functions like sorting. ![]() You will learn the R skills needed to answer essential questions about differences in crime across the different states. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. The first in our Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming. ![]()
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