Data Analysis in R: Basics and Beyond

This microcredential comprises two modules of this year's course program in Data Analysis:

Getting Started with R Software for Data Analysis
This introductory course provides a rigorous foundation in the R programming language, tailored for aspiring data analysts and researchers. Participants will learn how to navigate the R environment, import and manage datasets, and perform essential statistical analyses with clarity and precision. Emphasis is placed on developing a structured analytical mindset, enabling learners to move beyond basic usage toward writing reproducible, well-documented code. By the end of the course, students will be equipped to transform raw data into meaningful insights, laying the groundwork for more advanced data science applications.

Getting Started with R Software for Data Analysis

Leverage your R Skills: Data Wrangling, Plotting and Reporting with Tidyverse and Quarto
Building upon foundational R knowledge, this advanced course challenges participants to elevate their data analysis workflow through modern, efficient tools. Using the Tidyverse ecosystem, students will master sophisticated techniques for data wrangling, transformation, and visualization, transforming complex datasets into clear and compelling narratives. The course also introduces Quarto for dynamic reporting, enabling the seamless integration of code, analysis, and presentation into professional, reproducible documents. Learners are encouraged to adopt best practices in data storytelling, automation, and reproducibility—key competencies for high-impact analytical work in academic, business, and research environments.

Leverage your R Skills: Data Wrangling, Plotting and Reporting with Tidyverse and Quarto