Data Visualization and Transformation with R

Duke introduces data exploration through both the visual result and the transformations behind it. RStudio, Quarto and the tidyverse support a reproducible workflow, while ggplot2 and dplyr provide the main analysis tools. The provider estimates about thirteen hours.

What you will learn

• Match visual summaries to different types of data.
• Transform and summarize records with tidyverse tools.
• Prepare an analysis that another reader can reproduce.

Who this suits

Learners interested in an R-based analysis workflow that connects code, charts and explanation.

Before you enroll

The provider marks this beginner, with no prerequisite listed. Some reporting and version-control work is optional; check the current assignment choices.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Tool subscriptions, model API usage and cloud services may cost extra.

Put it into practice

Create a Quarto report from a small public dataset. Re-run it from a clean session and verify that the figures can be reproduced without manual edits.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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