R Programming Certifications and Certificates

Are you looking for a way to demonstrate your R programming skills? A certification or certificate course can be a great way to learn a new skill and find a new career. If you’re wondering what the difference is between a certificate and certification, how to choose the right course, or if pursuing a certificate in Data Science or a related field will help you get a job, then read below. You’ll find valuable information on what careers and industries are available to an R Programmer, what factors to consider when choosing a course, and a lengthy list of available certificates and training courses. 

While you may currently be on the fence about learning R, by the end of this article you should feel confident in your ability to pick the best course for you and begin your journey to becoming certified in R programming. 

What is R Programming?

R is a statistical programming tool that’s uniquely equipped to handle large amounts of data. Created by statisticians for statistical data analytics, this popular language has a range of applications for performing statistical computing and creating data visualizations. It is often used by Data Scientists, Business Analysts, Data Analysts, and those working in academia or science for tasks specifically involving statistical analysis. It can also now be used for AI, machine learning, financial analysis, and more.

R provides users with a range of graphical and statistical techniques, such as time-series analysis, clustering, classification, and linear and nonlinear modeling. One of the benefits of working with R is that it simplifies the process of creating publication-quality plots, especially those that incorporate formulas or mathematical symbols. This versatile language includes a fully integrated suite of software tools, such as a data storage and handling facility, operations for performing calculations on arrays, an integrated set of data analytics tools, and graphical tools designed to analyze and visualize data.

R is an open-source software environment, meaning it is publicly accessible and can be downloaded, modified, shared, and used for free by anyone. R was created to run on various UNIX platforms, Windows, and macOS. You can download R on The R Project for Statistical Computing’s website but, before downloading, you must choose your preferred CRAN mirror.

RStudio is an integrated development environment specifically for R that is also available as a free, open-source software environment. You must install R before using RStuido. The RStudio interface displays data tables, R code, graphs, and output, all in one place. Additionally, it offers a platform with which users can import Excel, CVS, SPSS, SAS, and Stata files into R without having to write a single line of code. RStudio Cloud is also available as a free download.

If you’re interested in learning more about R programming, check out Noble Desktop’s page about what R programming is and why you should learn it.

What Can You Do with R Programming?

R was created to primarily help with graphics and statistical computations. This language can accomplish various tasks, from data storage to data analysis to generating statistical models. Of all the available programming languages, R is considered to be the one with the most tools devoted exclusively to statistics. This language can aid with descriptive statistics tasks, like calculating standard deviations and designing models for mapping linear regression.

One of R’s most useful features is its ability to help users create customized data visualizations and dashboards. Some consider R’s ggplot2 package the best data visualization tool available. This package allows users to draw nearly any plot they can conceive. In addition, those who wish to take their data visualizations in R to the next level can combine ggplot2’s syntax with Plotly’s interactive features to make dashboards that are as engaging as they are interactive. 

R draws from various machine learning tools so that users can make accurate, data-driven predictions. Users can select from an array of machine learning models, which have applications for creating predictive models, such as movie recommendation systems and churn models. In addition, R users can automate reporting by using R Markdown documents. R Markdown offers a straightforward, accessible syntax to generate various reports, such as presentations, books, or other written documents. This helps R users easily communicate data analysis results with others. 

One of the many perks of R is that it has a large community that can assist as necessary with questions and other R-related topics. R users can seek advice from those who have completed similar projects or collaborate with other users. There are even data science contests available to test your skills in R programming. If you’re focused on data visualization, R offers packages like plotly, ggvis, and ggplot2, which are great resources for designing print-quality graphs. R’s package, Shiny, allows users to make their own dashboards and interactive web pages right from the R Console, which can then be hosted on any cloud service, like AWS.

R Programming Careers and Industries 

R boasts a full range of uses so it’s possible to find employment in a variety of fields. You could use your programming knowledge to work as a Data Scientist, a Data Analyst, or a Data Architect. You could also thrive in the fields of machine learning and software development; the career possibilities for an expert in R programming are abundant. Data Analysts work with R to locate, retrieve, and deliver data insights. Data Scientists commonly use R to create and implement the layout of a large dataset, as well as for tasks such as data mining, data modeling, research, and forecasting. As an R Programmer, you can also serve as a Database Administrator, or as a specialist or consultant in statistical computing. 

All of these roles exist across a variety of industries as well, meaning you aren’t tied to one specific field. Many major companies across a variety of industries require Data Scientists, Data Analysts, and Data Architects (among many other positions for which an R Programmer would be well-suited) like Amazon, Google, Accenture, and Cognizant. From tech to digital services to finance and healthcare, almost every industry will require these specific programming skills. 

Additionally, these roles tend to offer wages higher than the national average. According to the U.S. Bureau of Labor Statistics, Data Scientists make a median salary of around $103,500 per year. Plus, employment of data scientists is projected to grow 35 percent from 2022 to 2032, much faster than the average for all occupations. For Data Analysts, the average salary is around $64,000 but those in higher-ranking positions easily make over six figures. Data Architects are reported to make an average salary of about $125,000. While these are only a few select examples of possible job titles and career paths, they do show the potential for both long-term career growth and a sustainable living wage 

R Programming can also be implemented in a wide variety of fields. Geo Statisticians (specialists that predict weather, climate, pollution, and other atmospheric phenomena) use R to examine both spatial and spatiotemporal datasets. If you work as a Quantitative Analyst, you may sometimes use R to ensure clients’ financial portfolios are risk-balanced and apply mathematical models to identify new opportunities and evaluate asset prices. And, thanks to R’s data visualization capabilities, Data Visualization Analysts also use this language when they create and share interactive dashboards that are used to help policymakers make more informed decisions.

Will Being Certified in R Programming Help Me Find a Job?

While it isn’t required that you be certified in R for you to find a job and have a successful career, it can be extremely beneficial. Being knowledgeable in R may sometimes be enough, but often employers will want to see proof of your expertise. Certifications are more common in some occupations than others. Whether you need a certification may depend on your state, employer, or the type of work you hope to do. For data science, a common field for R programmers, many companies want to hire data professionals with data wrangling and analytical skills to manage and use the ever-increasing data pool. Data science certifications, like an R programming certificate, can prove that you have the necessary skills in advanced analytics to do the job.

A certificate and a portfolio of work are two pieces of evidence that show your aptitude, and both can be acquired through a certificate or certification program. According to Forbes, certificates tell prospective employers that you are capable of doing the job, make you marketable in nearly any sector, and help you earn more in the job of your choice.

Certifications vs. Certificates: What’s the Difference?

If you’re considering learning more about R programming to advance within your current career or to start a new job, you may consider pursuing a certification or certificate in this language. Knowledge and experience in the field are essential whether you are a college student looking for your first professional gig or an experienced worker trying to switch careers.

Programming certification courses can bridge the experience gap between graduating and getting hired and gaining certification in programming is a good way to show your prior work experience to hiring managers. Certifications typically involve a student signing up for an exam (administered by a third party), preparing for it, and then sitting for the test. Those who pass the exam earn certification in R, which is a great way to demonstrate mastery of this coding language. 

Certifications are often required by various employers to prove that you have continuing competency in ever-evolving tools and technology. They are a tried-and-tested method of proving one’s competence in a chosen field and, because of this, some employers will often cover the cost of these certifications and exams, eliminating the need for you to financially invest in this continuing education. 

On the other hand, a certificate in R is a completion-based program. Often offered by continuing education programs at colleges and universities, participants in certificate programs learn to use R for statistical computing tasks, data visualization, and other commonly used R tasks. You can also find certificate programs held by educational providers like Coursera, Udemy, and various others. These intensive programs are designed to make you well-versed in using R for a variety of real-world data tasks and often result in a portfolio of work that you can present to potential employers. 

Top Certifications & Certificates for R Programming

There are countless classes, courses, and trainings that could teach you the basics of R programming, but certifications and certificates can help offer a deeper level of knowledge and an industry-recognized certificate of completion. Below are some of the best virtual certificates and certifications available for R programming, including both on-demand and live.

edX’s Professional Certificate in Statistical Analysis in R provides two separate skill-building courses of self-paced R study: Basics of Statistical Inference and Modelling Using R and Advanced Statistical Inference and Modelling Using R. This certification covers basic statistical concepts, like confidence intervals, statistical inference, and hypothesis testing. Participants also receive instruction in generalized linear models, linear regression, and mixed effects of linear modeling. Led by a professor at Canterbury University, you’ll complete 5-10 hours of work per week. Offered on demand, this course allows extra flexibility as you can complete the lessons on your own time.

Udemy offers R Programming: Advanced Analytics in R for Data Science, a course of study geared toward those with basic R programming knowledge who wish to master more complex programming concepts. Over 50 lectures cover preparing data, working with date times and lists, applying functions instead of loops, and performing the median imputation method. Consisting of six hours of on-demand videos and seven articles, you can complete this course on your own time as there are no scheduled class hours. It’s recommended that prospective students have a basic knowledge of R, the GGPlot2 package, data frames, vectors, and vectorized operations.

The IBM Data Analytics with Excel and R Professional Certificate is a beginner-friendly certification module offered by IBM. It prepares students to work with Excel spreadsheets for data analysis and design relational databases and tables. Consisting of 10 hours of coursework per week, this training also covers tools like RStudio, Jupyter Notebooks, SQL, and both the Leaflet package and Shiny package for R. This course culminates with a capstone project where you’ll write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame, prepare data for modeling, interpret data, and build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

Udacity’s Programming for Data Science with R Certification helps students learn core data programming tools and concepts. This program was designed to prepare participants to enter a career in a data science-related field. You’ll learn to use SQL to answer complex business problems, including basic commands, joins, and aggregations. The Python section covers programming fundamentals and how to use libraries like NumPy and Pandas to work with data. You’ll also master Git and GitHub to manage versions of programs and collaborate with others. Each student will have access to career services including meaningful connections with industry professionals, honest, personalized feedback, and next steps from Udacity Career Coaches.

Coursera provides an intermediate course called R Programming Certification from Johns Hopkins University. This on-demand program consists of four modules that teach students how to work with R for data analytics tasks. Those enrolled work with basic R concepts, like accessing packages, writing functions, profiling code, debugging, and organizing code. You will learn how to install and configure the software needed for a statistical programming environment and describe generic programming language concepts in a high-level statistical language. You’ll earn a career certificate upon completion that you can add to your LinkedIn profile, resume, or CV. 

Coursera and Johns Hopkins also offer Data Science: Foundations using R Specialization, comprised of a five-course series that is ideal for beginners. Held entirely online with a flexible schedule, you’ll learn to use R to clean, analyze, and visualize data; ask the right questions, obtain data, and perform reproducible research; and use GitHub to manage data science projects. It’s best to take the first two courses in the prescribed order, but the rest you can choose to complete in whatever order you choose. You’ll receive a certificate of completion at the end that you can add to your LinkedIn. It’s recommended that you’re familiar with at least one, if not a few, other programming languages, but experience with R isn’t required. 

Harvard offers Data Science: R Basics, their first professional certificate in data science. You’ll use a real-world dataset about crime in the United States to learn the R skills needed to answer essential questions about differences in crime across the states. By building a strong foundation, you’ll be prepared for the more in-depth courses later in the series, which will cover concepts like probability, inference, regression, and machine learning. You’ll gain confidence and proficiency in R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

Duke University offers Financial Risk Management with R, an intermediate-level course that will teach you how to use the R programming language with Microsoft Open R and RStudio, utilizing their two main tools for calculating the market risk of stock portfolios: Value-at-Risk (VaR) and Expected Shortfall (ES). You’ll learn how to calculate the return of a portfolio of securities and quantify the market risk of that portfolio. This course is offered on-demand and is available in several languages. You’ll receive a certificate upon completion that can aid you in your application process. 

The University of Michigan (via Coursera) also has their own course: Arranging and Visualizing Data in R. Utilizing modalities like slide-based lectures, guided coding practice with the instructor, and independent practice, students will master the basics of R programming. The class will begin with step-by-step instructions on downloading and installing the software and how to navigate R and its companion, RStudio. You’ll then read data into the R environment and prepare it for summary and analysis while learning concepts like sorting rows of data, grouping by variables, summarizing over variables, pivoting, and creating new variables. Next, you’ll visualize your data, creating publication-ready plots with relatively little effort. Finally, you will master how to set up a project workflow for your own analyses.

Considered an intermediate course, it’s recommended you have some experience with R or other programming languages. You’ll receive your certificate upon completion which can be added to your LinkedIn or resume. 

NYC Data Science offers Data Science with R: Data Analysis and Visualization, which is designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll master how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. This course offers a theoretical framework to help understand the process of data analysis while also focusing on the practical tools needed in data analysis and visualization. By the end of the course, will be competent in the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes. Certificates are awarded at the end of the program at the satisfactory completion of the course, and it’s recommended that students have a basic knowledge of computer components and programming before starting. 

You could also try out the University of Washington’s Certificate in Statistical Analysis with R Programming through their professional and continuing education department. Comprised of three courses, this course will teach you to perform advanced data analysis and modeling using statistical models, tools, and R programming. You’ll learn the fundamentals of modern applied statistics for use in inference and prediction, gain skills in data mining and exploration, and discover how to produce insightful visualizations. You can purchase with a payment plan or pay in full upfront. 

Should I Get Certified in R Programming?

The decision of whether to seek R programming certification depends on several factors. When working in a data science-related field, some job listings seek individuals with a specific background in R. If you wish to demonstrate your R programming skills to a potential employer, certification or certificate study in R is one way to show that you’re able to use this open-source language in a professional setting. It may also distinguish you from other candidates who simply list “Proficient in R programming” on their resume but do not specify how they have achieved this proficiency. 

Deciding if certification is worth it for you will depend on what sort of outcomes are available. The O’Reilly Data Science Salary Survey in 2021 reported that the average salary for data and AI professionals who responded to the survey was $146,000 with the highest average compensation in California ($176,000). Moreover, the study revealed that many of these respondents acquired certifications with Cloud certifications, specifically in AWS and Microsoft Azure, most strongly associated with salary increases.

And, regardless of the course subject matter, most respondents participated in trainings of some form. Learning new skills and enhancing existing ones were the most common reasons for training, though the ability to be hired and job security were also factors. 

Ultimately, whether you decide to earn certification in R will depend on the job to which you apply, the employer’s specifications (and if they’ll pay for your certification), and what your specific goals are for compensation. While becoming certified in R programming may not be necessary for all potential jobs, proving your proficiency and commitment to growth can’t hurt your job searching process. 

How to Get Certified in R Programming

There are multiple ways to get certified in R Programming. If you’re already knowledgeable in R, you could take a certification exam to prove your skills. HackerRank offers two different exams: R (Basic) Skills Certification Test and R (Intermediate) Skills Certification Test

If you’re entirely new to R and looking to learn and get certified at the same time, there are many in-depth courses available online. Top educational providers like Udemy, Coursera, and Noble Desktop offer certificates in R. Those who enroll in a certificate program can earn industry-standard training that they can then apply in a professional setting. These courses can vary in length, subject matter, and cost, but all will boost your resume and set you apart from other candidates. 

You’ll typically take at least a few classes or modules, comprised of live instruction, recorded lessons, video tutorials, and/or independent projects. These projects are usually compiled into a final portfolio and your course will most likely end in either a final comprehensive project or an exam to prove your competency. 

By completing a rigorous certificate program in R or data science, you can demonstrate to employers that you are committed to studying programming and that you have the knowledge base and training to apply your skills to real-world datasets. And, if your course involved creating a portfolio, you can then use that collection of work to showcase your expertise to potential employers. 

How long will it take to become R Programming certified?

Each program or training will vary in length but, typically, professional certifications take anywhere from a few weeks to a few months to earn. Some, however, can take several years while others just require you to take a test without completing a program beforehand. A certification exam covers the fundamentals of the topic and lets you demonstrate competency. They're often required for certificates in information technology, healthcare, and business management.

Course length will also be dependent upon whether you attend full- or part-time. If you can attend a full-time program consisting of eight-hour class days, you can complete your training in a much shorter period of time. These courses, however, often aren’t convenient for those who work regular hours. A part-time program usually consists of live evening and weekend classes or on-demand sessions that can be completed when you desire. While part-time programs offer more flexibility, they tend to take at least double the amount of time as a full-time course. 

Knowing how much time you can commit to your learning is an important factor to consider when choosing a training. After all, your time is valuable and it’s important to make sure you use it as efficiently as possible. While full-time and part-time classes will have entirely different levels of commitment, it’s important to remember that both offer a quality education and can add value to your resume. 

How hard is it to become R Programming certified?

It’s no secret that R is known for being difficult to learn. R is vastly different from many programming languages, which is one of its many challenges. Additionally, the syntax of R, unlike languages like Python, is very difficult to read. Basic operations like selecting, naming, and renaming variables are more complicated in R than they are in other languages.

If you are already competent in basic data science principles and have some coding experience, you’ll probably experience fewer difficulties as you start learning R. But, even with previous experience, learning R still has its challenges. One survey of professional developers on StackOverflow found that 41.6 percent of professionals love R, while 58 percent of professionals dread it.

While R may be difficult to learn even if you have experience in other programming languages, having a mastery in Python, C++, JavaScript, or many other languages can still be helpful, especially when it comes to job hunting. Being able to show your versatility with multiple languages can give you an advantage in the application process.

R may be difficult to learn, but with dedication and hard work, you can become more familiar with the rules of the language. It may be challenging to learn the fundamentals, but once you’ve mastered the basic concepts, you’ll have the knowledge and mindset you need to explore more difficult concepts.

Learn R Programming with Hands-on Training at Noble Desktop

Noble Desktop has several excellent learning options for those new to R and courses for more advanced programmers interested in mastering complex R skills.

Noble’s Data Analytics with R Bootcamp is an immersive class that can be taken live online or in person in NYC. Designed to take participants from the basics of coding to a portfolio showcasing your experience working with R, you’ll master R basics like RStudio, libraries, variables, conditionals, looping, and applying. You’ll also learn SQL concepts to help you work with data, charts with GGPlot2, geo mapping with Leaflet, and graph networks with visNetwork. Those enrolled receive expert instruction and can retake the class for up to one year to brush up on course materials. 

Noble also offers a variety of in-person and live online coding classes that prepare participants to become Data Scientists or Web Developers. Courses are available in popular programming languages such as JavaScript and Python, as well as front end and full stack web development. Certificates are also offered in software engineering and data science. For students seeking instruction about using programming for finance technology, Noble currently has a FinTech bootcamp available as well, which includes one-on-one mentoring for all participants.

Noble Desktop’s in-person or live online Data Science Certificate prepares participants for exciting careers in data science and analysis. Live instruction is provided by industry experts on topics like creating machine learning models, performing data analysis with Python, and querying databases using SQL. You’ll also build and present dynamic dashboards and other data visualizations and learn to use Python's major plotting and dashboard libraries Matplotlib, Seaborn, Plotly, and Dash Enterprise. Through hands-on learning, you’ll eventually deploy your projects online with Github to demonstrate your analytical abilities to employers. 

They also offer Full Stack Web Development Certificate, a comprehensive course that uses projects to teach you how to code websites from scratch and build a portfolio of working web applications to showcase to potential employers. While this course won’t cover R programming, it will help you become a confident web developer who’s proficient in a variety of programming languages and tools like HTML/CSS, JavaScript, and the MERN tech stack (MongoDB, Express.js, React, and Node.js).

All Noble Desktop certificate students have the option of a free course retake and receive one-on-one mentoring as part of tuition. Payment plans and financing are available to help make the course more financially accessible. You can choose to attend full-time or part-time (the part-time classes are held in the evenings and on weekends to accommodate working professionals’ schedules).

In addition to the variety of programming courses Noble teaches, this top educational provider also has several in-person and live online Data Analytics classes. Noble’s Data Analytics Technologies Bootcamp is a beginner-friendly course that prepares students to work with core data analytics tools like SQL, Excel, and Tableau. In addition, a certificate in data analytics is also available for those interested in becoming a Business Analyst or Data Analyst. This rigorous learning opportunity prepares students to perform data analysis, statistical analysis, and data visualization, as well as how to use relational databases. All students receive one-on-one mentoring to help with their learning process.

Excel for Data Analytics is a short crash course that will help you gain hands-on experience and optimize your workflow for efficient data analysis. Held either in-person in NYC or live online, this course will help you improve your data analysis skills by learning essential functions, formulas, and advanced techniques like Pivot Tables and VLOOKUP. You’ll learn to sort, filter, group, and visualize data in Excel. The skills you learn in this course will complement any additional training you have or will complete in data analytics or R programming. 

They also offer Data Analytics Foundations, a beginner-friendly course that will teach you all the basics of data analytics, like descriptive statistics, inferential statistics, and data distributions. You’ll also study predictive analytics (forecasting, series forecast, correlation, and more), data visualizations (charts, icon sets, histograms, and moving averages, among others), probability, and prescriptive analytics. While this class is open to novices, it is recommended that you have an intermediate level of experience with Excel. This class can be taken online or in person in NYC and includes one free retake and class recordings. You’ll receive a certificate of completion at the end that you can add to your resume to help you in your job hunt.

How to Learn R Programming

Master R programming with hands-on training. Used commonly for data science and data analytics,R is free and open-source, making it a popular choice for programmers of all experience levels.

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