ºÚÁÏ´«ËÍÃÅ INFORMATION TECHNOLOGY
R Programming Language
R Programming Language
R is a popular programming language used for statistical computing and data analysis. As an open-source language, R can be used as a convenient, effective tool to process various statistical models and graphics.
Learning the fundamentals and applications of R at ºÚÁÏ´«ËÍÃÅ can prepare you for many careers in the IT and data analytics industries.
What Is R?
The R programming language was developed in the 1990s by University of Auckland professors Ross Ihaka and Robert Gentleman as a digital environment for statistical analysis. Though it began in an academic setting, R has since become a mainstay for data manipulation in all kinds of industries. R is a specific implementation of S—an older statistical language—that makes programming in statistical data and graphics available to all.
Programmers and statisticians turn to R when compiling, measuring, and modeling data with specific functions like vectors, objects, arrays, linear regression, time-series analysis, and more. R is particularly well suited to converting data into high-quality graphics, including models, plots, maps, and other detailed visualizations. Users can access R’s robust collection of software packages and RStudio—a dedicated R development environment—to make data science projects easier to organize and archive.
Why Is R Important?
R casts an undeniable influence on modern data and statistical analysis. Many organizations depend on R to identify patterns and project outcomes for growth. R is used in numerous industries and sectors, including the following:
- Finance
- Â Information technology
- Academic research
- Healthcare
- Business
- Government
- Social media
- Environmental science
- Retail
Virtually any company or institution today can take advantage of R to analyze business operations, conduct scientific research, predict consumer demand, identify market trends, and much more.
Users of R benefit from many features, including:
- Cross-platform compatibility
- Abundant package selection
- Supportive online community
- Detailed and well-developed syntax
- High degree of flexibility
Where Can You Use R?
R is primarily designed for statistical applications, and its versatility allows for its use in the following areas:
- Data analysis and modeling
- Data mining
- Machine learning
- Bioinformatics
- Data cleaning
- Statistical methodology
R is used by organizations both large and small for any number of applications, including risk assessment, stock market modeling, e-commerce data tracking, recordkeeping, advertising, and demand forecasting. IBM, Twitter, Bank of America, and Google are just some organizations that use R on a regular basis.
Why Choose ºÚÁÏ´«ËÍÃÅ to Learn R?
ºÚÁÏ´«ËÍÃÅ offers more than a dozen online, accredited bachelor’s and master’s programs in information technology. Each of our IT programs is designed with input from industry experts to ensure that you learn all you need to thrive in your career. These programs also include many in-demand IT certifications at no extra cost.
In addition, ºÚÁÏ´«ËÍÃÅ’s education model allows you to progress as quickly as you prove your knowledge, potentially saving time and money.
ºÚÁÏ´«ËÍÃÅÂ ºÚÁÏ´«ËÍÃÅ offers classes in the following programs where you can learn R:
Data Analytics – B.S.
Lean into data, and walk away with a cutting-edge online degree:...
Lean into data, and walk away with a cutting-edge online degree:
- °Õ¾±³¾±ð:Ìý62% of graduates finish within 36 months.
- Tuition and fees:Â $3,835 per 6-month term.
- °ä´Ç³Ü°ù²õ±ð²õ:Ìý39 total courses in this program.
Certifications in this program at no additional cost include:
- AWS Cloud Practitioner
- CompTIA Data+
- CompTIA Project+
- Udacity Nanodegree—a unique, highly recognized credential designed to prepare you for a career in data science
- MSI Change Management (Optional Certification)
- Certiprof Design Thinking Professional Certificate (Optional Certification)
Skills for your résumé that you will learn in this program:
- Data management
- Data wrangling
- Statistical analysis
- Visualization
- Leadership and managementÂ
- Model deployment & storytelling
Data Analytics – M.S.
Lead businesses with strong analysis skills:...
Lead businesses with strong analysis skills:
- Time:Â 61% of graduates finish within 20 months.
- °Õ³Ü¾±³Ù¾±´Ç²Ô:Ìý$4,520 per 6-month term.
- Courses:Â 11 total courses in this program.
This program consists of three specialization areas which allow you to gain specific experience and skills that will benefit your future career. You can choose from data science, data engineering, and decision process engineering specializations to enhance your degree.
Skills for your résumé that you will learn in this program:
- Data Modeling
- Big Data
- Business Intelligence
- Data Quality
- SQL
- Python
Find Your Degree
ºÚÁÏ´«ËÍÃÅ offers a flexible, competency-based learning model that empowers you to progress through courses as quickly as you master the material, potentially graduating faster and saving money.
Still not sure what degree course to pursue? Take our and get a degree course that aligns with your passions.