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  • R Programming

R Courses

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.


More to explore:

Popular R Courses and Certifications


  • J

    Johns Hopkins University

    R Programming

    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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    22K reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Introduction to R Programming for Data Science

    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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    613 reviews

    Beginner · Course · 1 - 3 Months

  • M

    Microsoft

    The R Programming Starter Course

    Skills you'll gain: Debugging, R Programming, Data Structures, Microsoft Development Tools, Software Documentation, Programming Principles, Development Environment, Data Manipulation, Data Transformation, Scripting

    5
    Rating, 5 out of 5 stars
    ·
    6 reviews

    Beginner · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Data Science: Foundations using R

    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    48K reviews

    Beginner · Specialization · 3 - 6 Months

  • M

    Microsoft

    Microsoft R Programming for Everyone

    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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    6 reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • I

    IBM

    Data Analysis with R

    Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Statistical Analysis, Data Analysis, Model Evaluation, Data Transformation, R Programming, Data Visualization, Regression Analysis, Predictive Modeling, Data Manipulation, Data Science, Box Plots, Statistical Modeling, Predictive Analytics, Correlation Analysis, Tidyverse (R Package), Data Cleansing, Data Preprocessing, Data Import/Export

    4.7
    Rating, 4.7 out of 5 stars
    ·
    368 reviews

    Intermediate · Course · 1 - 3 Months

What brings you to Coursera today?

  • E

    EDUCBA

    Analyze Data Using R for Statistical and Predictive Modeling

    Skills you'll gain: Data Visualization, Statistical Analysis, Predictive Modeling, R Programming, Data Manipulation, Business Analytics, Data Analysis, Probability & Statistics, Regression Analysis, Time Series Analysis and Forecasting, Case Studies, Decision Tree Learning, Data Structures

    Beginner · Course · 1 - 4 Weeks

  • The Google AI Certificate that powers your career

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  • D

    Duke University

    Data Analysis with R

    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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    7.7K reviews

    Beginner · Specialization · 3 - 6 Months

  • I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    43K reviews

    Beginner · Course · 1 - 3 Months

  • L

    Logical Operations

    R Programming for Data Science

    Skills you'll gain: R Programming, R (Software), Data Science, Data Analysis, Statistical Modeling, Data Visualization, Statistical Analysis, Regression Analysis, Statistical Visualization, Statistical Machine Learning, Plot (Graphics), Data Structures, Computer Programming, Decision Tree Learning, Machine Learning Methods, Machine Learning, Software Development, Computer Programming Tools, Data Import/Export, Machine Learning Algorithms

    Intermediate · Specialization · 1 - 3 Months

  • L

    Logical Operations

    R Programming: Data Analysis and Modeling

    Skills you'll gain: R Programming, R (Software), Plot (Graphics), Data Visualization, Statistical Visualization, Statistical Modeling, Data Analysis, Data Science, Statistical Analysis, Data Import/Export, Statistical Machine Learning, Machine Learning Methods, Machine Learning, Decision Tree Learning, Machine Learning Algorithms, Regression Analysis, Data Structures, Computer Programming, Computer Programming Tools, Software Development

    Mixed · Course · 1 - 3 Months

  • G

    Google

    Google Data Analytics

    Skills you'll gain: Data Storytelling, Rmarkdown, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Data Cleansing, Data Validation, Ggplot2, R (Software), Tableau Software, Sampling (Statistics), Presentations, Spreadsheet Software, Data Analysis, LinkedIn, Object Oriented Programming (OOP), Data Structures, Interviewing Skills, Applicant Tracking Systems

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    178K reviews

    Beginner · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

1234…426

In summary, here are 10 of our most popular r programming courses

  • R Programming: Johns Hopkins University
  • Introduction to R Programming for Data Science: IBM
  • The R Programming Starter Course: Microsoft
  • Data Science: Foundations using R: Johns Hopkins University
  • Microsoft R Programming for Everyone: Microsoft
  • Data Analysis with R: IBM
  • Analyze Data Using R for Statistical and Predictive Modeling: EDUCBA
  • Data Analysis with R: Duke University
  • Python for Data Science, AI & Development: IBM
  • R Programming for Data Science: Logical Operations

Skills you can learn in Data Analysis

Analytics (85)
Big Data (64)
Python Programming (47)
Business Analytics (40)
R Programming (37)
Statistical Analysis (36)
Sql (33)
Data Model (29)
Data Mining (27)
Exploratory Data Analysis (26)
Data Modeling (21)
Data Manipulation (20)

Frequently Asked Questions about R Programming

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:

  1. Preview the first module of many r programming courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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