This comprehensive course provides a complete introduction to R programming for data science. Learn statistical computing, data manipulation, visualization, and analysis techniques used by data scientists worldwide. Each session builds on fundamental concepts to help you master R for real-world data science applications.
Learn the fundamentals of R programming, RStudio IDE, and the core concepts of data science.
Master data importation, cleaning techniques, and exploratory data analysis to prepare datasets for analysis.
Learn powerful data manipulation techniques using dplyr to transform and organize your data efficiently.
Create professional, publication-quality graphics using ggplot2 and the Grammar of Graphics.
Learn statistical hypothesis testing methods including t-tests, chi-square tests, and correlation analysis.
Master correlation analysis and regression modeling to understand and predict relationships between variables.
Master R basics, data types, vectors, matrices, lists, and data frames
Transform and clean data using dplyr and other powerful R packages
Create stunning visualizations with ggplot2 and other graphics packages
Perform hypothesis testing, correlation, and regression analysis
Discover patterns and insights in your data through EDA techniques
Apply R skills to solve practical data science problems