Course Overview

Why do you need this course?

Data science has a strong presence in almost all businesses worldwide today as an essential decision-making tool. Internet-enabled devices (IoT) are generating data for these businesses in massive amounts and at an incredible pace. However, this accumulated raw data can’t be utilized by firms unless adequately processed. When suitably cleaned and processed, this raw data can be leveraged by data analytics tools to uncover hidden insights within datasets.

But how do we communicate the findings with our audience? The answer is through visuals. Why visuals? “A picture is worth a thousand words,” the famous quote by Frederick R. Barnard almost a century ago, stands true to date.

Our brains can undoubtedly process visual information significantly faster than text. For example, you have some data for median housing sales prices in $ for all US states that you want to present in a meeting. You can use a bar chart (a commonly used visual for categorical data) as shown below:

As you can see, it is easier to see the highest and lowest prices quickly with a bar chart. What if there was another visualization that could help you communicate the price range and correlate it to the state? Below is an advanced data visualization choropleth mapA choropleth map is a type of map that uses color to represent different data values. It is commonly used in studies and reports to help readers understand spatial data more effectively. that reveals exactly this information, and that too in a small space:

That is the power of data visualization.

Hence, it’s often the case that data science professionals within organizations use interesting visualizations. These visualizations help senior management in better decision-making.

Python and R, both incredibly popular programming languages, boast several powerful open-source data visualization libraries. Whatever programming language you use, the appropriate choice of data visualization is often what creates an impact when communicating data analysis findings to an audience.

Effective data visualizations can help you tell the story in your data. However, first, you’ll need to know how to use at least one data visualization tool.

About the course

R is used regularly by experts for data analysis. If you want to get started with data visualizations in R, this course shows you exactly how to use one of the most popular R packages— ggplot2. You’ll learn how to use the ggplot2 package to modify visualizations using colors, themes, and even the legends on your graph.

What makes the course unique?

• This beginner-friendly course is designed to provide comprehensive and precise basics for mastering data visualizations using the ggplot2 package in R.

• Even if you already know some basics of the ggplot2 package, this course is a good refresher.

• The course also provides you examples to practice and meaningful quizzes to assess your learning progress to boost your confidence.

This completes the first lesson, which highlights the importance of building effective data visualizations in data science and why you should learn the ggplot2 package in R.