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    • R

    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

    • Status: Free
      Free
      U

      University of Leeds

      Statistical Methods

      Skills you'll gain: Exploratory Data Analysis, Statistical Methods, Statistical Modeling, Data Collection, Statistics, Statistical Inference, R Programming, Probability, Data Analysis, Probability Distribution, Simulations, Statistical Visualization, Descriptive Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Building React Application using ASP.NET MVC5

      Skills you'll gain: Restful API, ASP.NET, .NET Framework, Application Programming Interface (API), JavaScript Frameworks, Web Services, Secure Coding, JSON, React.js, Server Side, Object-Relational Mapping, Application Frameworks, Model View Controller, Web Applications, Routing Protocols, Authentications, Authorization (Computing), Data Validation

      4
      Rating, 4 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      S

      SkillUp EdTech

      Java Development with Databases 

      Skills you'll gain: Hibernate (Java), Object-Relational Mapping, Spring Boot, Restful API, Java, NoSQL, Database Development, Databases, SQL, Database Design, Java Programming, Data Access, Database Management, Relational Databases, Back-End Web Development, Query Languages

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Statistics and Data Analysis with Excel, Part 2

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Sampling (Statistics), Statistical Methods, Microsoft Excel, Probability & Statistics, Data Analysis, Regression Analysis, Probability Distribution

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Statistical Methods for Computer Science

      Skills you'll gain: Network Analysis, R Programming, Statistical Analysis, Regression Analysis, Statistical Modeling, Statistical Methods, Combinatorics, Bayesian Network, Statistical Hypothesis Testing, Data Analysis, Probability, Probability & Statistics, Bayesian Statistics, Probability Distribution, Simulations, Data Science, Markov Model, Applied Mathematics, Graph Theory, Statistics

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Applied Math for Materials Science and Engineering

      Skills you'll gain: Integral Calculus, Calculus, Engineering Calculations, Advanced Mathematics, Applied Mathematics, Mathematical Theory & Analysis, Engineering Analysis, General Mathematics, Mathematical Modeling, Differential Equations, Derivatives

      Intermediate · Course · 1 - 4 Weeks

    • I

      Infosec

      C++ Superpowers and More

      Skills you'll gain: Secure Coding, Application Security, System Programming, C++ (Programming Language), C (Programming Language), Unix, Embedded Systems, Debugging, Operating Systems, Data Security, Linux

      3.9
      Rating, 3.9 out of 5 stars
      ·
      11 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of California, Santa Cruz

      Bayesian Statistics: Capstone Project

      Skills you'll gain: Bayesian Statistics, Technical Communication, R Programming, Statistical Analysis, Statistical Modeling, Data Analysis, Advanced Analytics, Time Series Analysis and Forecasting, Markov Model, Statistical Methods, Predictive Modeling, Sampling (Statistics), Probability Distribution

      Advanced · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Advanced Reproducibility in Cancer Informatics

      Skills you'll gain: Code Review, GitHub, Git (Version Control System), Version Control, Docker (Software), Software Development Tools, Containerization, Bioinformatics, Health Informatics, Science and Research, Automation, Medical Science and Research, Technical Communication

      Advanced · Course · 1 - 3 Months

    • U

      Università di Napoli Federico II

      Python per la Data Science

      Skills you'll gain: PyTorch (Machine Learning Library), NumPy, Image Analysis, Pandas (Python Package), Matplotlib, Artificial Neural Networks, Deep Learning, Computer Vision, Keras (Neural Network Library), Jupyter, Data Manipulation, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Python Programming, Data Science, Scikit Learn (Machine Learning Library)

      4.3
      Rating, 4.3 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      M

      Microsoft

      Full-Stack Developer Capstone Project

      Skills you'll gain: ASP.NET, Restful API, Full-Stack Web Development, Performance Tuning, .NET Framework, Application Programming Interface (API), Cloud Development, Data Modeling, Development Environment, Cloud Applications, Software Development Tools, Object-Relational Mapping, Application Deployment, Web Development, Software Development, Cloud Infrastructure, Web Applications, UI Components, Back-End Web Development, Cloud Platforms

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Learn Spring Boot in 100 Steps - Beginner to Expert

      Skills you'll gain: JUnit, Apache Maven, Spring Framework, Spring Boot, Build Tools, Restful API, Unit Testing, Hibernate (Java), Integration Testing, Gradle, Java, Object-Relational Mapping, Software Testing, Bootstrap (Front-End Framework), Database Management, UI Components, Web Applications, Application Programming Interface (API), Application Frameworks, Test Case

      4.3
      Rating, 4.3 out of 5 stars
      ·
      6 reviews

      Intermediate · Specialization · 1 - 3 Months

    R learners also search

    Data
    Data Analysis
    Data Science
    Data Analytics
    Analysis
    R Programming
    Beginner Data Analysis
    Beginner Data Analysis
    1…414243…48

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

    • Statistical Methods: University of Leeds
    • Building React Application using ASP.NET MVC5: Board Infinity
    • Java Development with Databases : SkillUp EdTech
    • Statistics and Data Analysis with Excel, Part 2: University of Colorado Boulder
    • Statistical Methods for Computer Science: Johns Hopkins University
    • Applied Math for Materials Science and Engineering: Korea Advanced Institute of Science and Technology(KAIST)
    • C++ Superpowers and More: Infosec
    • Bayesian Statistics: Capstone Project: University of California, Santa Cruz
    • Advanced Reproducibility in Cancer Informatics: Johns Hopkins University
    • Python per la Data Science: Università di Napoli Federico II

    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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