R courses can help you learn data manipulation, statistical analysis, data visualization, and programming fundamentals. You can build skills in creating reproducible research, performing regression analysis, and implementing machine learning algorithms. Many courses introduce tools like RStudio and packages such as ggplot2 and dplyr, which enhance your ability to analyze datasets and present findings effectively.

Johns Hopkins University
Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Programming Principles, Data Manipulation, Data Structures, Performance Tuning, Data Import/Export
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Data Visualization, Statistical Programming, Data Visualization Software, Data Cleansing, Data Manipulation, Data Import/Export, Data Structures
Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Manipulation, Web Scraping, R Programming, Data Analysis, Data Science, Data Structures, Data Import/Export, Exploratory Data Analysis, Programming Principles, Jupyter, Integrated Development Environments
Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Model Evaluation, R Programming, Data Manipulation, Data Visualization, Predictive Analytics, Statistical Analysis, Data Science, Regression Analysis, Statistical Modeling, Data Cleansing, Data Preprocessing, Feature Engineering, Forecasting
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Plot (Graphics), Statistical Programming, Statistical Visualization, Ggplot2, R (Software), Dimensionality Reduction, Data Visualization Software, Data Integration, Knitr, Data Sharing, GitHub, Machine Learning
Beginner · Specialization · 3 - 6 Months

Microsoft
Skills you'll gain: Debugging, R Programming, Data Structures, Microsoft Development Tools, Software Documentation, Programming Principles, Development Environment, Data Manipulation, Data Transformation, Scripting
Beginner · Course · 1 - 4 Weeks

Microsoft
Skills you'll gain: Rmarkdown, Version Control, Web Scraping, Regression Analysis, Knitr, Exploratory Data Analysis, Statistical Analysis, Data Manipulation, Dimensionality Reduction, Ggplot2, Geospatial Information and Technology, Time Series Analysis and Forecasting, Plotly, Microsoft Azure, Data Cleansing, Data Visualization, Software Documentation, R Programming, Data Quality, Microsoft Copilot
Beginner · Professional Certificate · 3 - 6 Months
Duke University
Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Peer Review, Regression Analysis, R (Software), Statistical Reporting, Probability Distribution, Statistical Analysis, Statistics, Data Analysis Software, Data Analysis, Probability & Statistics, Probability, R Programming, Statistical Modeling, Statistical Methods, Data Visualization
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
Beginner · Course · 1 - 3 Months
Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Database Design, Shiny (R Package), Data Visualization, Data Wrangling, Dashboard, Exploratory Data Analysis, Relational Databases, Data Analysis, Ggplot2, Model Evaluation, Data Presentation, SQL, Plot (Graphics), Databases, Data Manipulation, Web Scraping, R Programming
Beginner · Specialization · 3 - 6 Months

Coursera
Skills you'll gain: R (Software), Data Import/Export, Package and Software Management, R Programming, Data Structures, Data-oriented programming, Statistical Programming, Data Analysis Software, Data Analysis, Data Science
Beginner · Guided Project · Less Than 2 Hours

Johns Hopkins University
Skills you'll gain: Rmarkdown, Shiny (R Package), Ggplot2, Tidyverse (R Package), Data Visualization, Spatial Data Analysis, Statistical Visualization, Scatter Plots, Plot (Graphics), Dashboard, Data Import/Export, Interactive Data Visualization, R Programming, Data Visualization Software, Geospatial Information and Technology, Data Literacy, Statistical Reporting, Storyboarding, Data Science, Data Analysis
Beginner · Specialization · 3 - 6 Months
R programming is a language and environment specifically designed for statistical computing and data analysis. It is widely used among statisticians, data analysts, and researchers for its powerful capabilities in data manipulation, statistical modeling, and visualization. The importance of R programming lies in its ability to handle complex data sets and perform advanced analyses, making it a valuable tool in various fields, including finance, healthcare, and academia.
With skills in R programming, you can pursue various job roles such as data analyst, statistician, data scientist, and research analyst. These positions often require a strong understanding of data manipulation and analysis, as well as the ability to communicate findings effectively. Industries such as technology, finance, and healthcare are particularly keen on professionals who can leverage R to derive insights from data.
To learn R programming effectively, you should focus on several key skills. These include understanding the basics of programming concepts, data structures, and functions in R. Additionally, familiarity with data visualization libraries like ggplot2, data manipulation packages like dplyr, and statistical modeling techniques will enhance your proficiency. Knowledge of the R ecosystem and how to use R for data analysis is also crucial.
Some of the best online courses for R programming include the Introduction to R Programming for Data Science and the Data Analysis with R Programming. These courses provide foundational knowledge and practical skills that can help you get started with R programming and apply it to real-world data analysis.
Yes. You can start learning r programming on Coursera for free in two ways:
If you want to keep learning, earn a certificate in r programming, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn R programming, start by selecting a beginner-friendly course that covers the basics. Engage with interactive exercises and projects to apply what you learn. Utilize online resources, such as forums and documentation, to enhance your understanding. Consistent practice and real-world application of R will help solidify your skills and boost your confidence in using the language.
Typical topics covered in R programming courses include data types and structures, functions, control flow, data visualization, and statistical analysis. Advanced courses may explore topics like machine learning, data wrangling, and the use of R packages for specific applications. Understanding these topics will provide a comprehensive foundation for using R in various data-related tasks.
For training and upskilling employees in R programming, courses like the Microsoft R Programming for Everyone Professional Certificate and the Expressway to Data Science: R Programming and Tidyverse Specialization are excellent choices. These programs are designed to equip learners with practical skills that can be directly applied in the workplace.