Data Manipulation and Cleaning in R for Beginners

Raw data is rarely ready for analysis, often containing missing values, inconsistent formatting, and structural issues. This text-based course guides you from raw data confusion to structured data clarity using R, one of the most powerful languages for data science. You will learn how to efficiently import, filter, reshape, and clean datasets to uncover reliable insights. What you'll learn: - Understand foundational data structures and clean coding principles in R - Import and parse diverse data formats using modern tidyverse packages - Filter, arrange, and mutate data frames to isolate key insights - Handle missing values and inconsistent data types systematically - Reshape and merge complex datasets for streamlined analysis - Apply clean-code best practices with modern package management workflows We begin with essential terminology and core R concepts before moving step-by-step through real-world data manipulation scenarios using tidyverse tools. This program is designed specifically for beginners, requiring no prior data cleaning experience. Start mastering your data workflows today.