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    Results for "r"

    • Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Statistical Programming, Data Visualization Software, Data Cleansing, Data Manipulation, Exploratory Data Analysis, Data Import/Export, Package and Software Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • Johns Hopkins University

      R Programming

      Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export

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

      Intermediate · Course · 1 - 4 Weeks

    • Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Coursera Project Network

      Getting Started with R

      Skills you'll gain: Data Import/Export, Package and Software Management, R Programming, Data Structures, Data Literacy, Software Installation, Data Analysis Software

      4.3
      Rating, 4.3 out of 5 stars
      ·
      379 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • 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, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

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

      Beginner · Specialization · 3 - 6 Months

    • IBM

      Applied Data Science with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Shiny (R Package), Data Wrangling, Dashboard, Exploratory Data Analysis, Relational Databases, Data Analysis, Ggplot2, Database Design, Data Presentation, SQL, Plot (Graphics), Leaflet (Software), Data Transformation, Database Management, Data Manipulation, Web Scraping, R Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • 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
      ·
      562 reviews

      Beginner · Course · 1 - 3 Months

    • Johns Hopkins University

      Data Visualization & Dashboarding with R

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

      4.8
      Rating, 4.8 out of 5 stars
      ·
      429 reviews

      Beginner · Specialization · 3 - 6 Months

    • IBM

      Data Analysis with R

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Data Transformation, R Programming, Data Manipulation, Data Visualization, Box Plots, Predictive Analytics, Statistical Analysis, Regression Analysis, Statistical Modeling, Correlation Analysis, Data Cleansing, Tidyverse (R Package), Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      332 reviews

      Intermediate · Course · 1 - 3 Months

    • 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, Data Literacy, Data Analysis, R Programming, Descriptive Statistics, Statistical Software, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Statistical Programming, Statistics, Statistical Methods, Public Health, Probability & Statistics, Epidemiology, Statistical Modeling

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

      Beginner · Specialization · 3 - 6 Months

    • IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Data Visualization Software, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Presentation, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free

      Universidad Nacional Autónoma de México

      Introducción a Data Science: Programación Estadística con R

      Skills you'll gain: R Programming, Statistical Programming, Ggplot2, Data Manipulation, Simulations, Statistical Software, Data Science, Data Visualization, Graphing, Programming Principles, Data Import/Export, Scripting, Data Structures, Software Installation, Package and Software Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      8.5K reviews

      Beginner · Course · 1 - 3 Months

    Searches related to r

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    1234…48

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

    • Data Analysis with R Programming: Google
    • R Programming: Johns Hopkins University
    • Data Analysis with R: Duke University
    • Getting Started with R: Coursera Project Network
    • Data Science: Foundations using R: Johns Hopkins University
    • Applied Data Science with R: IBM
    • Introduction to R Programming for Data Science: IBM
    • Data Visualization & Dashboarding with R: Johns Hopkins University
    • Data Analysis with R: IBM
    • Statistical Analysis with R for Public Health: Imperial College London

    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

    R programming courses on Coursera offer learners an opportunity to master a wide array of skills essential for data analysis, statistical computing, and graphical representation, including:

    • Fundamentals of R syntax and programming environment
    • Data manipulation and cleaning techniques using R packages like dplyr and tidyr
    • Statistical analysis and model building to interpret complex data sets
    • Creating compelling visualizations with ggplot2 and other visualization tools
    • Developing reproducible reports and interactive web apps with R Markdown and Shiny
    • Applying R in various domains such as finance, healthcare, and academic research ‎

    Coursera’s R programming courses are designed to welcome learners at different levels of expertise:

    • No prior programming experience is required for introductory courses, which focus on the basics of R and general programming concepts.
    • Intermediate courses are suitable for learners with some programming background, enhancing their data manipulation and analysis skills.
    • Advanced courses cater to experienced users seeking to deepen their expertise in statistical methods, machine learning, or R package development.‎

    Coursera’s R programming courses are designed to welcome learners at different levels of expertise:

    • No prior programming experience is required for introductory courses, which focus on the basics of R and general programming concepts.
    • Intermediate courses are suitable for learners with some programming background, enhancing their data manipulation and analysis skills.
    • Advanced courses cater to experienced users seeking to deepen their expertise in statistical methods, machine learning, or R package development.‎

    Engaging in R programming courses on Coursera can lead to several forms of recognition that highlight your skills and dedication:

    • Course Certificates: These certificates demonstrate your success in individual R programming courses, showcasing your skills in specific aspects of the language.
    • Professional Certificates: Obtain these by completing a series of courses that prepare you for data analysis and statistical roles using R.
    • Specializations: Deepen your proficiency with comprehensive course sequences that focus on specific areas such as statistical analysis, machine learning, or advanced data visualization with R. ‎

    Looking to enhance your team's R programming skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our R programming training options and make a purchase, please visit our Coursera for Teams page.‎

    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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