Introduction to R Programming for Data Science

IBM begins with the R environment and common data structures, then adds program flow and file operations. The roughly twelve-hour sequence finishes with a project, providing a programming foundation before specialized analysis or visualization courses.

What you will learn

• Choose between vectors, lists, factors and data frames.
• Write functions and control execution with conditions and loops.
• Import data from common formats into an R workflow.

Who this suits

New R learners who want a broad programming introduction with data-oriented examples.

Before you enroll

The provider labels the course beginner and does not specify prerequisites. Check the demonstrations for your preferred RStudio or notebook environment.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Tool subscriptions, model API usage and cloud services may cost extra.

Put it into practice

Write a function that imports a small CSV file, checks its required columns and returns a summary. Test an empty file and a missing value.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

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