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.