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    • R Programming

    R Programming Courses Online

    Master R programming for statistical computing and data analysis. Learn about R syntax, data manipulation, and visualization techniques.

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    Explore the R Programming Course Catalog

    • I

      Imperial College London

      Statistical Analysis with R for Public Health

      Skills you'll gain: Analytical Skills, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Quantitative Research, Exploratory Data Analysis, Probability & Statistics, Statistics, Statistical Methods, Data Wrangling, Biostatistics, Time Series Analysis and Forecasting, Probability Distribution, Predictive Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Visualization with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Dashboard, Statistical Visualization, Ggplot2, Plot (Graphics), Shiny (R Package), R Programming, Leaflet (Software), Scatter Plots, Box Plots, Spatial Data Analysis, Histogram, UI Components, Server Side, Application Deployment

      4.6
      Rating, 4.6 out of 5 stars
      ·
      259 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      Get Started with Python

      Skills you'll gain: Object Oriented Programming (OOP), Data Analysis, Data Structures, Jupyter, Python Programming, NumPy, Pandas (Python Package), Computer Programming, Programming Principles, Scripting, Data Processing, Data Manipulation, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.5K reviews

      Advanced · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data Visualization & Dashboarding with R

      Skills you'll gain: Rmarkdown, Shiny (R Package), Ggplot2, Tidyverse (R Package), Data Visualization, Spatial Data Analysis, Scatter Plots, Plot (Graphics), Dashboard, Data Import/Export, Data Visualization Software, Interactive Data Visualization, R Programming, Geospatial Information and Technology, Statistical Reporting, Plotly, Statistical Visualization, Data Storytelling, Heat Maps, Data Manipulation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      429 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Introduction to R Programming and Tidyverse

      Skills you'll gain: Rmarkdown, Ggplot2, Tidyverse (R Package), Statistical Visualization, R Programming, Data Visualization Software, Statistical Programming, Data Manipulation, Data Analysis, Data Transformation, Software Installation, Development Environment

      4.2
      Rating, 4.2 out of 5 stars
      ·
      46 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Presentation, Data Wrangling, Data Visualization, SQL, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Big Data, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, Pandas (Python Package), Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      91K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • J

      Johns Hopkins University

      Mastering Software Development in R

      Skills you'll gain: Ggplot2, Software Documentation, Open Source Technology, Tidyverse (R Package), Package and Software Management, Web Scraping, Data Manipulation, Data Visualization Software, Leaflet (Software), R Programming, Data Visualization, Technical Documentation, Datamaps, Data Cleansing, Interactive Data Visualization, Object Oriented Programming (OOP), GitHub, Version Control, Debugging, Functional Design

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      GPU Programming

      Skills you'll gain: Artificial Neural Networks, Image Analysis, Event-Driven Programming, C and C++, Scalability, Applied Machine Learning, Deep Learning, Natural Language Processing, Artificial Intelligence and Machine Learning (AI/ML), Performance Tuning, Linear Algebra, Distributed Computing, Computer Hardware, Mathematical Software, Computer Vision, Computer Architecture, Computer Systems, Data Structures, Performance Testing, System Programming

      Build toward a degree

      2.7
      Rating, 2.7 out of 5 stars
      ·
      145 reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Data Science, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Visualization, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Introductory C Programming

      Skills you'll gain: Debugging, Maintainability, Programming Principles, Algorithms, Software Testing, Program Development, C (Programming Language), Pseudocode, Computational Thinking, Software Engineering, Simulations, System Programming, Data Structures, Software Development, Computer Programming, Command-Line Interface, Development Environment, Development Testing, User Interface (UI), Interactive Design

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Statistical Reporting, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    R Programming learners also search

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    1234…287

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

    • Statistical Analysis with R for Public Health: Imperial College London
    • Data Visualization with R: IBM
    • Get Started with Python: Google
    • Data Visualization & Dashboarding with R: Johns Hopkins University
    • Introduction to R Programming and Tidyverse: University of Colorado Boulder
    • IBM Data Analyst: IBM
    • Mastering Software Development in R: Johns Hopkins University
    • GPU Programming: Johns Hopkins University
    • Introduction to Probability and Data with R: Duke University
    • Data Science: Johns Hopkins University

    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 the use of the R computer language for statistical analysis and graphic presentation. R is commonly used in business and research computing environments to analyze and visualize data, then create reports that can be used for decision making. R programming is increasingly more important given the expansion of big data for analysis.‎

    It's important to learn R programming if you want to be able to build computer programs that wrangle data and convert it into usable information. Organizations often have large amounts of data but are unable to understand what it means. Using programs written by R, you can generate Bayesian statistics and graphic analysis for business analytics, public health, and medical research, among other industries. Learning R is a component of learning data science, so another reason to study R programming is to get some of the fundamentals completed before venturing deeper into computer science studies.‎

    Typical careers that use R programming are in business analytics, financial services, and medical research. It is also a skill used in many data science roles. R programming pulls out information from large sets of data, so any field that calls for statistical inference from big data needs competent R programmers to create the analytics and reports needed. Some experience with R programming is useful for people who will be managing programming teams or requesting reports made from programs written in R. As big data analysis becomes more important in more fields, R programming becomes more valuable in the workplace.‎

    Online courses can help you learn R programming by introducing the fundamentals of the language, teaching how it connects to such industries as finance and health care, and offering projects that let you show what you have learned. Courses are offered at all levels, from beginning to advanced. Many of them set you up for further work in data science or allow you to earn a specialization or certificate.‎

    Online R Programming courses offer a convenient and flexible way to enhance your knowledge or learn new R Programming skills. Choose from a wide range of R Programming courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in R Programming, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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