Apply Exploratory Data Analysis with R and ggplot2
About this course
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. This project-based course guides learners through a complete EDA workflow, starting from understanding datasets and variable types to creating professional-quality visualizations using the grammar of graphics. Learners will analyze univariate and bivariate data, customize plots for clarity, detect outliers, and visually assess linear relationships using regression techniques. Each concept is reinforced through hands-on practice with real-world data scenarios. What makes this course unique is its strong emphasis on practical visualization-driven analysis, not just theory. Learners gain experience producing production-ready plots and interpreting analytical results in a way that supports data-driven decision-making. This course is ideal for aspiring data analysts and professionals who want to strengthen their EDA, data visualization, and analytical storytelling skills using R.
75/100
CourseAsk score
- What the provider tells you
- 39/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understand data structure
- identify patterns in data
- visualize relationships using ggplot2
- evaluate linear trends through regression
- create professional-quality visualizations
Course objectives
- develop skills in exploratory data analysis (EDA)
- customize plots for clarity
- detect outliers and assess linear relationships
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