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Data Visualization in R

Updated 03/2026
Bring your data into focus with data visualizations in R using ggplot2. Learn the graphical and plot-building skills to tell better data stories.
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RData Visualization12 hr23,625

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Track Description

Data Visualization in R

Unlock Insights with Data Visualization in R

Bring your data to life and master data visualizations with R and ggplot2. In this Track, you'll develop the essential skills needed to analyze and display data effectively, allowing you to communicate insights and discoveries to non-technical stakeholders. Through hands-on practice, you'll learn how to use ggplot2 to create, customize, and enhance a wide range of visualizations.

From Beginner to Data Visualization Expert

Whether you're new to data visualization or looking to expand your skills, this Track has you covered. You'll start by learning the fundamental principles of the grammar of graphics, the foundation of ggplot2. As you progress, you'll explore intermediate features such as facets, coordinate systems, and statistics, enabling you to create more complex and informative plots.

Create Stunning Visualizations with ggplot2

Discover how to:
  • Produce meaningful and visually appealing plots using ggplot2
  • Customize plots with colors, themes, and labels to highlight key insights
  • Use facets to display multiple plots simultaneously for easy comparison
  • Apply coordinate systems to handle different data types and plot requirements
  • Incorporate statistical analysis directly into your visualizations

Best Practices for Effective Data Storytelling

In the final course, you'll dive into data visualization best practices in R. Learn how to choose the right chart type for your data and audience, explore alternative visualization techniques, and enhance your plots with perception-driven style improvements. You'll also discover three common plot types to avoid and how to replace them with more effective alternatives.

Advance Your Data Science Career

Data visualization is a critical skill for data scientists, analysts, and researchers. By completing this Track, you'll be equipped to:
  • Create compelling data narratives that influence decision-making
  • Collaborate effectively with stakeholders across your organization
  • Stand out in the job market with in-demand data visualization expertise
  • Explore advanced topics in data visualization and visual analytics
Whether you're a data professional looking to enhance your skillset or a beginner seeking to launch a career in data science, this Track will provide you with the tools and knowledge to excel in data visualization using R and ggplot2.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Data Visualization with ggplot2

    Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

  • Course

    5

    Visualization Best Practices in R

    Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Data Visualization in R
3 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, the Data Visualization Track is suitable for beginners. The courses in this track are arranged in order from introductory to more intermediate levels. This allows new users to slowly get up to speed with R and ggplot2.

What is the programming language of this Track?

This Data Visualization Track is programmed in R.

Which jobs will benefit from this Track?

This Data Visualization Track is especially beneficial to data scientists, analytics professionals, data engineers, and business intelligence professionals.

How will this Track prepare me for my career?

Completing this Data Visualization Track will give you the practical skills to use ggplot2 to share insights and discoveries with non-technical stakeholders. You will understand how to tell better data stories using ggplot2 in R to create stunning data visualizations.

How long does it take to complete this Track?

This Data Visualization Track usually takes 12 hours to complete, this includes several courses that significantly upskill users.

What's the difference between a skill track and a career track?

Career Tracks are comprehensive and project-oriented where, as a user, you build a portfolio of data science projects and get feedback from experts. Skill tracks are more focused on practicing and mastering domain-specific skills so they can be used in real-world. Data Visualization is a Skill Track.

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