The statistics-first language. Base R basics, vectors, factors, lists, data frames, the RStudio IDE, R Projects, R Markdown / Quarto, the tidyverse (dplyr, tidyr, readr, purrr, stringr, lubridate, forcats), pipe operators (%>% and |>), ggplot2 (geoms, aesthetics, scales, themes, facets), data import (read_csv, readxl, haven, googlesheets4), joins & pivots (pivot_longer/wider), summarising & group_by, mutate & transmute, slicing & arrange, tibbles, dates & times with lubridate, strings & regex with stringr, factors with forcats, functional programming with purrr (map, walk, reduce), tidymodels (rsample, recipes, parsnip, yardstick, workflows), statistical modeling (lm, glm, mixed models, GAM), survival analysis, time series (forecast, fable), Shiny dashboards, plotly, leaflet, sf for geospatial, data.table (the speed alternative), arrow & Parquet, reproducible reports with knitr/Quarto, package development with devtools/usethis/testthat, and the R OpenSci ecosystem. 30 units, 450 lessons.