R
Full course · 21 lessonsR is the definitive language for statistical computing, data analysis, and visualization. It powers academic research, data science, and machine learning workflows worldwide. These are the definitive free resources — vetted, current, and complete.
Getting Started with R
Console, scripts, RStudio, and the R execution model.
Values and Types
Numeric, integer, character, logical — and special values.
Variables and Scoping
Assignment, object names, environments, and existence checks.
Arithmetic and Operators
Numeric, comparison, logical, and vectorized operators.
Functions
Definitions, defaults, return values, and anonymous functions.
Vectors and Indexing
Atomic vectors, naming, logical subsetting, and sequences.
Control Flow
if/else, ifelse, for, and while loops.
Strings and Text
paste, sprintf, string functions, and regular expressions.
Lists, Matrices, and Data Frames
Heterogeneous containers and tabular data.
Factors, Dates, and Attributes
Categorical variables, ordered factors, and time handling.
The Apply Family
apply, lapply, sapply, tapply, and friends.
Advanced Functions
Reuse, ... arguments, closures, and lexical scoping.
The Tidyverse
dplyr, ggplot2, readr, and tidyr — the modern R.
Data Visualization
Base R plots, histograms, boxplots, and saving output.
Errors and Exceptions
stop, warning, tryCatch, and input validation.
File I/O
Reading and writing CSV, text, and modern formats.
Statistics and Sampling
Sampling, distributions, summaries, and hypothesis tests.
Missing Data
NA propagation, na.rm, and imputation strategies.
Grouping and Aggregation
table, aggregate, split, and group_by + summarize.
Functional Programming and OOP
First-class functions, environments, S3 and S4 classes.
Ecosystem and Next Steps
CRAN, R Markdown, Shiny, and the road ahead.
Free Books
R for Data Science (2nd Edition)
The gold standard for starting R. Teaches importing, tidying, transforming, visualizing, and modeling data using modern tidyverse workflows.
Advanced R (2nd Edition)
The definitive text for intermediate-to-advanced R — functional programming, metaprogramming, and performance optimization.
An Introduction to Statistical Learning (ISLR)
A classic machine learning textbook available as free PDF with practical R labs in every chapter.