R Programming for Data Science, Machine Learning, and Shiny Apps

Organizations across the globe rely on data to make critical decisions, and R is one of the most powerful languages designed specifically to translate raw data into actionable insights. This structured text-based course takes you from absolute beginner to confident data practitioner, teaching you how to write clean, efficient R code. You will start by understanding fundamental programming concepts and data structures, then quickly transition to advanced data manipulation, modern visualization, and machine learning. By reading through practical explanations and studying clear code snippets, you will gain the skills to build predictive models, handle deep learning concepts, and design interactive web applications to share your findings. What you'll learn: - Understand R syntax, foundational data structures, and modern package management. - Manipulate and clean messy datasets using tidyverse principles and modern data workflows. - Create clear, professional data visualizations to communicate complex trends and insights. - Build and evaluate statistical machine learning models, from simple regressions to deep learning concepts. - Develop interactive web applications and dashboards using the Shiny framework. - Apply modern tidymodels workflows for structured, reproducible machine learning pipelines. The course flows naturally from basic R syntax and data manipulation to advanced statistical modeling and interactive application deployment. You will progress from writing your first line of code to structuring production-ready data science projects. This course is designed for beginners who want to learn data science and R programming from scratch, with no prior coding experience required. Start your journey into data science and learn how to turn raw numbers into interactive, data-driven applications today.