Learners will develop the ability to explore, visualize, and interpret data using R, ggplot2, and linear analysis techniques to generate meaningful insights. By the end of this course, learners will confidently apply exploratory data analysis (EDA) methods to understand data structure, identify patterns, visualize relationships, and evaluate linear trends.
Apply Exploratory Data Analysis with R and ggplot2
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
6 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Perform exploratory data analysis using R to understand data structure and patterns.
Create clear, professional visualizations using ggplot2 and the grammar of graphics.
Analyze and interpret linear relationships using regression and visual analysis techniques.
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
February 2026
Assessments
8 assignments
Taught in English
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There are 2 modules in this course
This module introduces learners to the core principles of Exploratory Data Analysis using R and ggplot2. Learners explore dataset structure, variable types, and initial data inspection techniques, and then apply the grammar of graphics to create meaningful visualizations that support data-driven insights.
What's included
10 videos4 assignments
This module focuses on enhancing visual analysis and uncovering relationships within data using advanced ggplot2 techniques. Learners analyze univariate and bivariate distributions, identify patterns and trends, visualize linear relationships, interpret regression results, and synthesize insights for effective communication.
What's included
9 videos4 assignments
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