R Programming: Foundations of Data Analysis and Modeling

Data is only as valuable as your ability to analyze and interpret it. R is a premier language built specifically for statistical computing, data visualization, and predictive modeling. This text-based course guides you from R novice to confident data analyst. You will learn how to handle datasets, perform exploratory data analysis, and implement foundational statistical models to extract meaningful insights. What you'll learn: Understand core R syntax, variables, and essential data structures like vectors and data frames; Import and clean raw datasets from various file formats to prepare them for analysis; Manipulate and transform data efficiently using modern tidyverse principles and dplyr; Create clear, informative data visualizations to communicate statistical trends; Build and interpret foundational statistical models, including linear and logistic regression; Apply best practices for structuring data science workflows and documenting your code. The curriculum begins with fundamental R terminology and environment setup before progressing to data manipulation, visualization, and predictive modeling. Each concept is reinforced with clear written explanations and practical code examples. This course is designed for absolute beginners to programming and data science; no prior experience with R or statistics is required. Start your journey into data science and unlock the power of R today.