Data Analysis with R: Wrangling, Visualization, and Reporting

Moving beyond basic R programming is the key to unlocking powerful data science capabilities. To work with real-world datasets, you need efficient tools to clean, transform, and communicate your findings clearly. This text-based course guides you through intermediate R techniques, helping you transition from writing simple scripts to building structured, reproducible data workflows. You will learn how to handle large-scale data, craft expressive visualizations, and compile professional reports directly from your code. What you'll learn: Understand the core concepts of tidy data and modern R package ecosystems; Manipulate and transform complex datasets efficiently using dplyr pipelines; Process high-volume data quickly with the powerful data.table syntax; Create clear, customized data visualizations to reveal hidden insights; Generate dynamic, reproducible documents and reports using R Markdown; Apply best practices for clean, readable, and maintainable R code. The course begins with foundational concepts of data manipulation and the philosophy behind modern R packages. You will then progress through step-by-step written tutorials covering data transformation, advanced plotting, and automated document generation. This course is designed for learners who have a basic familiarity with R syntax and want to elevate their data analysis skills. No advanced programming or statistical background is required. Start reading today to transform raw data into polished, professional reports.