A practical, beginner-friendly path to using R for data science. You will learn core R syntax, data structures, importing and cleaning data, the tidyverse (dplyr, tidyr), visualization with ggplot2, control flow and functions, reproducible workflows, and a gentle introduction to statistics and modeling. Each chapter builds on the last with concise examples and best practices for writing clear, eff...
No prior programming required; a computer with internet access and willingness to practice are sufficient.
15 modules — work at your own pace.
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