Data Analytics for the Public Sector with R

Navigating the complexities of public sector data requires a specific set of analytical skills and tools to turn raw information into actionable policy insights. This course provides the foundational knowledge needed to process, analyze, and interpret public administration data using the R programming language. You will learn how to handle the unique challenges of government datasets while building a reproducible workflow that ensures transparency and accuracy. By the end of this course, you will be able to transform messy public datasets into clear summaries that drive evidence-based decision-making. You will transition from understanding basic data structures to writing your own logic for complex demographic analysis. What you'll learn: - Understand the essential vocabulary of public administration and data-driven policy - Apply core R programming concepts and modern syntax for efficient data management - Manipulate large datasets using tidyverse libraries to filter, mutate, and summarize information - Create reusable functions to streamline the analysis of population and demographic data - Practice modern data ethics and the principles of reproducible research in a government context The course begins with an introduction to key terminology and foundational R concepts before moving into practical text-based exercises focused on real-world public sector scenarios. You will progress through structured lessons that emphasize clean code and logical data transformations. This course is designed for beginners, including policy analysts, public administrators, and students who have no prior experience with programming or R. Start building your data-driven career in the public sector today.