Data Science Pipeline and Statistical Inference with ModernDive

In the modern data-driven world, turning raw information into actionable insight requires a structured approach. This course introduces you to the entire data science pipeline, guiding you through the essential steps of importing, tidying, transforming, and modeling data. You will gain a clear understanding of how to make sense of complex datasets using modern statistical inference. By reading through practical, text-based guides and studying real-world code examples, you will transform from a data novice into an analyst who can confidently interpret patterns and draw valid conclusions. What you'll learn: Understand the core stages of the data science pipeline from data import to final communication; Apply tidyverse principles to clean and transform messy datasets efficiently; Learn statistical inference concepts using modern, simulation-based approaches; Practice exploratory data analysis to discover hidden patterns in your data; Build and interpret simple linear regression models to make predictions; Structure your data workflows using virtual environments and modern package management tools. This text-only course begins with foundational concepts and definitions, ensuring you grasp the core terminology before moving on to hands-on analysis and modeling workflows. This course is designed specifically for beginners with no prior experience in statistics or programming. Start your journey into data science and master the modern analytical pipeline today.