Free ebookR Programming for Data Analysis: The Practical Starter Guide

Course Description

R Programming for Data Analysis: The Practical Starter Guide is a hands on ebook course designed to help you start using R for real data work from day one. If you want a reliable path into data science and business intelligence, this course builds the core R programming foundations you need to explore data, answer questions, and communicate results with clarity.

You will learn how to work confidently with data frames and modern tibbles, including indexing and inspection techniques that make it easier to understand what your dataset contains. You will also practice importing real world files into R, bringing in CSV, Excel, and text data so you can move from messy inputs to analysis ready tables. As you progress, you will apply tidy data principles with dplyr to clean, transform, and summarize information in ways that match typical analytics tasks in Information Technology environments.

The course then connects everyday data preparation to practical integration workflows by reshaping and combining datasets with joins, bindings, and pivoting. You will turn insights into clear visuals using ggplot2, creating charts that support decision making in business intelligence. Finally, you will learn an efficient reporting workflow with R Markdown, moving from analysis to shareable results that are easy to reproduce and update.

To bring everything together, you will complete an end to end R data analysis project that mirrors real workplace scenarios, helping you build confidence and a reusable workflow. Start the course today and begin turning raw data into actionable insight with R.