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    R 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 Course Catalog

    • K

      King Abdullah University of Science and Technology

      Fundamental Skills in Bioinformatics

      Skills you'll gain: Statistical Analysis, Bioinformatics, Unix, Scientific Visualization, Statistical Methods, R Programming, Rmarkdown, Unix Commands, Data Analysis, Data Quality, Statistical Hypothesis Testing, Exploratory Data Analysis, Data Visualization, Programming Principles, Pandas (Python Package), Python Programming, NumPy, Data Manipulation, Data Structures

      4.4
      Rating, 4.4 out of 5 stars
      ·
      59 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Davis

      Principles of Secure Coding

      Skills you'll gain: Secure Coding, Application Security, Software Design, Programming Principles, Debugging, Program Development, Computer Programming, C (Programming Language), Software Development Methodologies

      4.4
      Rating, 4.4 out of 5 stars
      ·
      367 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      RStudio for Six Sigma - Basic Descriptive Statistics

      Skills you'll gain: Sampling (Statistics), Statistical Methods, Descriptive Statistics, Data Visualization, Data Import/Export, Pareto Chart, Histogram, Statistical Analysis, Six Sigma Methodology, Box Plots, R Programming, Probability Distribution, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      64 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      Skills you'll gain: Statistical Inference, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, R Programming, Data Ethics, Statistical Methods, Data Analysis, Statistical Analysis, Data Modeling, Predictive Modeling, Probability & Statistics, Advanced Analytics, Correlation Analysis, Forecasting, Data Science, A/B Testing, Machine Learning, Classification And Regression Tree (CART), Linear Algebra

      Build toward a degree

      4.1
      Rating, 4.1 out of 5 stars
      ·
      52 reviews

      Intermediate · Specialization · 3 - 6 Months

    • L

      LearnQuest

      Java Enterprise Edition

      Skills you'll gain: Java Platform Enterprise Edition (J2EE), Application Deployment, Web Applications, Application Servers, Java, Object-Relational Mapping, Application Development, Web Development, Web Servers, Application Frameworks, Scripting, Middleware, Server Side, Javascript and jQuery, Data Storage, Apache Tomcat, Enterprise Architecture, Data Sharing, Hypertext Markup Language (HTML), Model View Controller

      4.6
      Rating, 4.6 out of 5 stars
      ·
      210 reviews

      Intermediate · Specialization · 1 - 3 Months

    • J

      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistical Analysis, Applied Mathematics, Advanced Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      187 reviews

      Advanced · Course · 1 - 3 Months

    • I

      Imperial College London

      Infectious Disease Modelling

      Skills you'll gain: Epidemiology, Mathematical Modeling, Statistical Modeling, Simulations, Infectious Diseases, R Programming, Public Health, Differential Equations, Statistical Methods

      4.8
      Rating, 4.8 out of 5 stars
      ·
      293 reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free
      Free
      N

      National Taiwan University

      計算機程式設計 (Computer Programming)

      Skills you'll gain: Programming Principles, Computer Programming, C (Programming Language), Data Structures, Computer Science, Algorithms, Program Development, Command-Line Interface, Functional Design, Debugging, Data Validation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      367 reviews

      Mixed · Course · 1 - 3 Months

    • E

      EDUCBA

      IoT Enabled Farming

      Skills you'll gain: Internet Of Things, Big Data, Data Management, Wireless Networks, Predictive Analytics, Emerging Technologies, Data-Driven Decision-Making, Real Time Data, Automation, Environmental Science, Data Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      160 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Instructor Network

      Root Cause Analysis: Principles and Benefits

      Skills you'll gain: Root Cause Analysis, Operational Efficiency, Corrective and Preventive Action (CAPA), Continuous Improvement Process, Product Quality (QA/QC), Process Improvement, Operational Excellence, Proactivity, Complex Problem Solving

      4.5
      Rating, 4.5 out of 5 stars
      ·
      69 reviews

      Beginner · Course · 1 - 4 Weeks

    • É

      École Polytechnique

      Photovoltaic solar energy

      Skills you'll gain: Data Storage Technologies, Electrical Power, Electrical Systems, Energy and Utilities, Environmental Science, Project Finance, Power Electronics, Semiconductors, Economics, Basic Electrical Systems, Environment and Resource Management, Electrical Engineering, Chemical Engineering, Chemistry

      4.2
      Rating, 4.2 out of 5 stars
      ·
      474 reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Data Science Capstone

      Skills you'll gain: Exploratory Data Analysis, Predictive Modeling, Data Science, Data Analysis, Data Presentation, Data Collection, Data Storytelling, Data Cleansing, Statistical Analysis, Data Manipulation

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

      Mixed · Course · 1 - 3 Months

    R learners also search

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    1…222324…48

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

    • Fundamental Skills in Bioinformatics: King Abdullah University of Science and Technology
    • Principles of Secure Coding: University of California, Davis
    • RStudio for Six Sigma - Basic Descriptive Statistics: Coursera Project Network
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • Java Enterprise Edition: LearnQuest
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
    • Infectious Disease Modelling: Imperial College London
    • 計算機程式設計 (Computer Programming): National Taiwan University
    • IoT Enabled Farming: EDUCBA
    • Root Cause Analysis: Principles and Benefits: Coursera Instructor Network

    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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