Applied Data Science with R for Beginners

Data is one of the most valuable assets in the modern world, yet turning raw numbers into actionable insights requires the right set of tools and analytical thinking. This text-based course introduces you to the R programming language, the tool of choice for data analysts and statistical researchers worldwide. You will start with the absolute basics of data structures, learn to clean messy datasets, and progress to building predictive models. By completing this course, you will transition from a programming novice to a confident data explorer who can manipulate datasets and communicate insights effectively. What you'll learn: - Understand foundational R syntax, data types, and basic programming logic - Clean and transform raw datasets using modern tidyverse packages - Create professional data visualizations to communicate key patterns and trends - Apply basic statistical methods and exploratory data analysis techniques - Build and evaluate simple predictive models using modern modeling workflows - Practice writing clean, reproducible R scripts and organizing data projects This course begins with essential terminology, core data structures, and the fundamentals of the R environment. From there, you will move step-by-step through importing data, performing exploratory analysis, and implementing foundational machine learning concepts. This course is designed specifically for beginners, with no prior programming experience or advanced statistical background required. Start reading today to unlock the potential of your data with R.