Basics of R Programming for Data Analytics

Data analytics begins with clean, structured, and well-understood data. To get there, you need a reliable programming language that is purpose-built for statistical computing and data manipulation. This course offers a clear, structured path to learning R from the ground up, designed specifically for those with no prior coding experience. You will transition from a complete beginner to a confident data explorer, capable of writing clean R scripts to solve real-world data problems. By learning the fundamental syntax and modern data manipulation techniques, you will gain the skills necessary to prepare raw data for meaningful analysis. What you'll learn: - Understand core programming concepts in R including variables, data types, and vectors - Import and clean raw datasets using modern tidyverse packages like readr and dplyr - Write reproducible R scripts utilizing clean code conventions and pipe operators - Manipulate data frames to filter, arrange, group, and summarize complex datasets - Handle missing data and perform basic exploratory data analysis - Apply functional programming basics to automate repetitive data tasks This course begins with foundational concepts, defining key terminology, installing your environment, and running your first commands. You will then progress step-by-step through data structures, modern data wrangling workflows, and basic statistics. This course is designed for absolute beginners, aspiring data analysts, and professionals looking to transition into data science without any prior programming knowledge. Start your data journey today and learn the essential language of data analysis.