Data Visualization and Transformation with R

Instructor: Mine Çetinkaya-Rundel , Dr. Elijah Meyer

Beginner Level • 1 week to complete at 10 hours a week • Flexible Schedule

What You'll Learn

                Transform, visualize, summarize, and analyze data in R, with packages from the Tidyverse, using RStudio
Carry out analyses in a reproducible and shareable manner with Quarto
Learn to effectively communicate results through an optional written project version controlled with Git and hosted on GitHub

            

Skills You'll Gain

R Programming
Data-Driven Decision-Making
Data Visualization Software
Data Science
Statistical Analysis
Data analysis
Git (Version Control System)
Descriptive Statistics
Data Manipulation
Data Transformation
Data Visualization
Statistics
Probability &amp; Statistics
Exploratory Data Analysis
Tidyverse (R Package)
Data Wrangling
Statistical Programming
Ggplot2
GitHub

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

                    
                                Learn new concepts from industry experts
                            
                                Gain a foundational understanding of a subject or tool
                            
                                Develop job-relevant skills with hands-on projects
                            
                                Earn a shareable career certificate

There are 3 modules in this course

Hello World! In the first module, you will learn about what data science is and how data science techniques are used to make meaning from data and inform data-driven decisions. There is also discussion around the importance of reproducibility in science and the techniques used to achieve this. Next, you will learn the technology languages of R, RStudio, Quarto, and GitHub, as well as their role in data science and reproducibility.

In our second module, we'll advance our understanding of R to set the stage for creating data visualizations using tidyverse’s data visualization package: ggplot2. We'll learn all about different data types and the appropriate data visualization techniques that can be used to plot these data. The majority of this module is to help best understand ggplot2 syntax and how it relates to the Grammar of Graphics. By the end of this module, you will have started building up the foundation of your statistical tool-kit needed to create basic data visualizations in R.

In this module, we will take a step back and learn about tools for transforming data that might not yet be ready for visualization as well as for summarizing data with tidyverse’s data wrangling package: dplyr. In addition to describing distributions of single variables, you will also learn to explore relationships between two or more variables. Finally, you will continue to hone your data visualization skills with plots for various data types.