Data Visualization
Master data visualization with R. Learn ggplot2, EDA, and advanced techniques for compelling insights.
Master data visualization with R. Learn ggplot2, EDA, and advanced techniques for compelling insights.
This course equips data scientists with essential skills in producing and interpreting digital maps, charts, and graphs. Students will learn principles, concepts, techniques, and tools for visualizing complex data sets using R. The curriculum covers the grammar of graphics, color theory, and Exploratory Data Analysis (EDA) idioms. Hands-on experience with ggplot2 allows students to create various visualizations, from basic histograms to advanced interactive and spatial visualizations. The course emphasizes critical evaluation of visualization designs and practical skills in R. A final project enables students to apply their knowledge to create a compelling data story through visualization.
Instructors:
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What you'll learn
Understand the principles and components of effective data visualization
Master the use of R and ggplot2 for creating various types of data visualizations
Apply color theory and design principles to enhance visual representations of data
Create and interpret common Exploratory Data Analysis (EDA) idioms like histograms and box plots
Develop skills in arranging multiple plots and creating interactive visualizations
Learn to embed images and tables in R Markdown for comprehensive data reports
Skills you'll gain
This course includes:
182 Minutes PreRecorded video
9 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides a comprehensive introduction to data visualization, focusing on using R and ggplot2. Students will learn the fundamentals of data visualization, including the grammar of graphics, color theory, and principles of effective visual design. The curriculum covers a range of visualization techniques, from basic histograms and scatter plots to more advanced topics like interactive visualizations and spatial mapping. Hands-on experience with R and ggplot2 allows students to create various types of visualizations and gain practical skills in data exploration and presentation. The course emphasizes critical thinking about visualization choices and their impact on data interpretation. By the end of the course, students will be able to create compelling, informative visualizations that effectively communicate insights from complex datasets.
Introduction to Data Visualization and Getting Started with R
Module 1 · 5 Hours to complete
Graphics Components for Data Visualization
Module 2 · 1 Hours to complete
ggplot2
Module 3 · 3 Hours to complete
Embed Images and Tables in R Markdown Files
Module 4 · 2 Hours to complete
Boxplot and Multiple-view Layout
Module 5 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Assistant Teaching Professor of Geography
Aihua Li is a teaching assistant professor in the Department of Geography and Meteorology and the Data Science program at Ball State University. Dr. Li’s research focuses on interdisciplinary geospatial sciences within environmental and ecological contexts. Her work involves the analysis, modeling, and visualization of extensive geospatial data across various scales.
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