This course provides a comprehensive introduction to R language fundamentals and its practical applications in bioinformatics, designed for absolute beginners. The first part covers the origin of R (based on S language), software download and installation, and the layout of the RStudio integrated development environment. The second part details the installation channels for extension packages (CRAN, Bioconductor, GitHub) and loading methods (library/require), along with strategies for accessing help documentation (?, ??) and recommended learning resources. The third part systematically explains R data types and structures, including vectors, factors, arrays, matrices, data frames, and lists, with operations for creation and manipulation; it also covers variable naming rules, conditional statements (if/ifelse), loops (for/while), and writing custom functions. The fourth part focuses on file I/O, demonstrating functions such as scan, read.table/read.csv/read.delim for reading different data formats, and save.image, write.table for saving results. The fifth part centers on the ggplot2 package, using the mpg example dataset to illustrate step‑by‑step creation of scatter plots, histograms, bar charts, pie charts, boxplots, violin plots, and density curves, along with fine‑tuning techniques for axes, colors, faceting, and themes. The course concludes with practical exercise recommendations. Throughout, the emphasis is on combining theory with hands‑on practice, providing an essential R programming foundation for advanced bioinformatics analyses such as transcriptomics and gene family studies.