R Programming Basics for Data Science and Visualization

Data-driven decision-making starts with the right programming foundation. R is one of the most powerful languages built specifically for statistical analysis, data manipulation, and stunning visual storytelling. This text-based course guides you from absolute beginner to a confident data analyst. You will learn how to write clean R code, manipulate complex datasets, and generate meaningful insights through practical, written examples. What you'll learn: - Understand foundational R syntax, variables, data types, and core programming concepts. - Import and clean messy datasets using modern tidyverse packages like dplyr. - Create professional data visualizations using the powerful ggplot2 library. - Apply tidy data principles to structure and organize your datasets efficiently. - Perform exploratory data analysis to uncover hidden trends and patterns. - Write reproducible reports to document your analytical workflow. You will start with the fundamental terminology of R and basic programming structures. From there, you will progress through step-by-step written explanations and structured code snippets, learning how to clean real-world data, perform statistical summaries, and build clear, communicative charts. This course is designed for absolute beginners, aspiring data scientists, and business analysts who want a solid, code-first introduction to R. No prior programming or statistical experience is required. Start reading today and build a strong foundation in modern R programming.