Data Analysis with R Programming (Google)

Colleagues, the Data Analysis with R Programming training will teach you how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. This course is part of Google Data Analytics Professional Certificate program. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. 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. Describe the R programming language and its programming environment. Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors. Describe the options for generating visualizations in R. Demonstrate an understanding of the basic formatting in R Markdown to create structure and emphasize content. Obtain crucial skills in Data Analysis, R Markdown, Data Visualization, R Programming and RStudio. Training modules include: 1) Programming and data analytics - Introduction to the exciting world of programming, Fun with R, Carrie: Getting started with R•3 minutes, Programming languages, Introduction to R, Intro to RStudio, 2) Programming using RStudio - Programming using RStudio, Programming fundamentals, Operators and calculations, The gift that keeps on giving, Welcome to the tidyverse, Use pipes to nest code, Connor: Coding tips, 3) Working with data in R - Data in R, R data frames, Working with data frames, Cleaning up with the basics, Organizing your data, Transforming data, Same data, different outcome, The bias function, 4) More about visualizations, aesthetics, and annotations - Visualizations in R•2 minutes, Visualization basics in R and tidyverse, Getting started with ggplot, Joseph: Career path to people analytics, Enhancing visualizations in R, Doing more with ggplot, Aesthetics and facets, Annotation layer, Saving your visualizations, 5) Documentation and Reports - Documentation and reports, Overview of R Markdown, Using R Markdown in RStudio, Structure of markdown documents, Meg: Programming is empowering, Code chunks and Exporting documentation.

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