Data Visualization with R: Principles and Practice
Master data visualization principles and create compelling visualizations using ggplot2 in R for effective data communication.
Master data visualization principles and create compelling visualizations using ggplot2 in R for effective data communication.
This comprehensive course explores fundamental data visualization principles and their practical application using ggplot2 in R. Students learn to create effective visualizations through real-world case studies in global health, economics, and infectious diseases. The course emphasizes critical evaluation of data quality, addressing common visualization mistakes, and detecting systematic errors. Participants develop skills in exploratory data analysis and learn to create custom plots that effectively communicate data-driven insights. The curriculum combines theoretical principles with hands-on practice, preparing students to leverage data visualization for impactful analysis and communication.
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What you'll learn
Master fundamental data visualization principles
Create custom plots using ggplot2 in R
Effectively communicate data-driven findings
Identify and avoid common visualization mistakes
Apply visualization techniques to real-world case studies
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This introductory data visualization course equips students with essential skills for creating effective and meaningful data visualizations. The curriculum covers fundamental visualization principles, focusing on proper communication of data-driven findings. Students learn to use ggplot2, a powerful R package, to create custom plots and explore real-world datasets. The course addresses common visualization pitfalls and teaches critical evaluation of data quality. Through case studies in health, economics, and disease trends, participants gain practical experience in creating impactful visualizations.
Fee Structure
Instructor
32 Courses
Harvard Biostatistics Professor and Genomics Data Analysis Pioneer
Rafael Irizarry is a distinguished Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and Professor of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute. His expertise spans genomics, data analysis, and the R programming language. Irizarry's career has been marked by significant contributions to the field of genomics data analysis over the past two decades
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