The 6 best R courses in 2026

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examp

The course "Computational and Graphical Models in Probability" equips learners with essential skills to analyze complex systems through simulation techniques and network analysis. By exploring advanced concepts such as Exponential Random Graph Models and Probabilistic Graphical Models, students will learn to model and interpret intricate social structures and dependencies within data. What sets this course apart is its emphasis on practical applications using the R programming language, empowering students to simulate random variables effectively and construct sophisticated models for real-wo

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression mo

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" to

This course continues our gentle introduction to programming in R designed for 3 types of learners. It will be right for you, if: • you want to do data analysis but don’t know programming • you know programming but aren’t too familiar with R • you know some R programming but want to learn more about the tidyverse verbs It is best taken following the first course in the specialization or if you already are familiar with ggplot, RMarkdown, and basic function writing in R. You will use learn to use readr to read in your data, dplyr to analyze your data, and stringr and forcats to man

Google's job-ready data analytics path: spreadsheets, SQL, Tableau, R, and data storytelling.