Earlier, you learned how to find Base R packages using the function install packages. You can follow along on your own, using your RStudio cloud account. You'll find lots of tutorials and examples related to the tidyverse online that show you these principles and how they're applied to data analytics. The principles associated with tidyverse, which you'll learn both here and at your job, have been widely adopted by the R community. It's one of the reasons why tidyverse is considered a key part of programming for most R users. On top of that, the community support for tidyverse is strong too. I realized that the more I put into learning about the tidyverse, the more I get out of it. That's when I got even more excited about working in R. I understood the basics, but now I was finding out how the tidyverse improves on the basics. It felt like I was stepping into a more advanced zone of R. I started learning about tidyverse when I was working on a survey project. The packages in tidyverse work together naturally. Using tidyverse can help you work your way through pretty much the entire data analysis process.
Tidyverse is actually a collection of packages in R with a common design philosophy for data manipulation, exploration, and visualization. And for lots of data analysts, at the top of the list of useful packages is tidyverse. Packages offer a helpful combination of code, reusable R functions, descriptive documentation, tests for checking operability, and sample data sets. As we discussed earlier, packages are a big part of what makes R so great. Learn about R Markdown for documenting R programming. Discover the options for generating visualizations in R. Gain an understanding of dataframes and their use in R. Explore the contents and components of R packages including the Tidyverse package. Explore the fundamental concepts associated with programming in R. Discover how to use RStudio to apply R to your analysis. Examine the benefits of using the R programming language. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. This course will also cover the software applications and tools that are unique to R, such as R packages. You’ll find out how to use RStudio, the environment that allows you to work with R. In this course, you’ll learn about the programming language known as R. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs.
This course is the seventh course in the Google Data Analytics Certificate.
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