Data Analysis with R Programming (Coursera)

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, you will:

- Examine the benefits of using the R programming language.

- Discover how to use RStudio to apply R to your analysis.

- Explore the fundamental concepts associated with programming in R.

- Explore the contents and components of R packages including the Tidyverse package.

- Gain an understanding of dataframes and their use in R.

- Discover the options for generating visualizations in R.

- Learn about R Markdown for documenting R programming.

What You Will Learn

- 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 R Markdown to create structure and emphasize content

Course 7 of 8 in the Google Data Analytics Professional Certificate.

Syllabus

WEEK 1

Programming and data analytics

R is a programming language that can help you in your data analysis process. In this part of the course, you’ll learn about R and RStudio, the environment you’ll use to work in R. You’ll explore the benefits of using R and RStudio as well as the components of RStudio that will help you get started.

WEEK 2

Programming using RStudio

Using R can help you complete your analysis efficiently and effectively. In this part of the course, you’ll explore the fundamental concepts associated with R. You’ll learn about functions and variables for calculations and other programming. In addition, you'll discover R packages, which are collections of R functions, code and sample data that you’ll use in RStudio.

WEEK 3

Working with data in R

The R programming language was designed to work with data at all stages of the data analysis process. In this part of the course, you’ll examine how R can help you structure, organize, and clean your data using functions and other processes. You’ll learn about data frames and how to work with them in R. You’ll also revisit the issue of data bias and how R can help.

WEEK 4

More about visualizations, aesthetics, and annotations

R is a tool well-suited for creating detailed visualizations. In this part of the course, you’ll learn how to use R to generate and troubleshoot visualizations. You’ll also explore the features of R and RStudio that will help you with the aesthetics of your visualizations and for annotating and saving them.

WEEK 5

Documentation and reports

When you’re ready to save and present your analysis, R has different options to consider. In this part of the course, you’ll explore R Markdown, a file format for making dynamic documents with R. You’ll find out how to format and export R Markdown, including how to incorporate R code chunks in your documents.