Get an overview of R and its ecosystem, understanding its role in data science and statistical analysis.

Learn to install R and RStudio, navigate the interface, and write your first lines of R code.

Explore fundamental data structures in R, including vectors, lists, and data frames.

Master vector creation, manipulation, and vectorized operations for efficient data processing.

Understand matrices, their properties, and operations for working with two-dimensional data structures in R.

Grasp core programming concepts in R, including control flow (if-else, loops) and functions for logical problem-solving.

Deep dive into data frames, R’s most popular structure for tabular data, covering creation, subsetting, and manipulation.

Learn essential techniques for cleaning, transforming, and reshaping data in R using various built-in functions and packages.

Create compelling data visualizations using R’s powerful plotting capabilities, including base graphics and ggplot2.

Apply methods for summarizing and visualizing data to uncover patterns, detect anomalies, and test hypotheses.

Understand the principles of hypothesis testing and perform common statistical tests in R to draw data-driven conclusions.

Learn to build and interpret linear regression models in R to analyze relationships between variables and make predictions.