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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

    • Status: Free Trial
      Free Trial
      U

      University of Washington

      Practical Predictive Analytics: Models and Methods

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Big Data

      4.1
      Rating, 4.1 out of 5 stars
      ·
      320 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      C

      Codio

      Intro to Operating Systems 2: Memory Management

      Skills you'll gain: Operating Systems, C (Programming Language), Performance Tuning, System Programming, Virtualization and Virtual Machines, Linux

      4.7
      Rating, 4.7 out of 5 stars
      ·
      55 reviews

      Advanced · Course · 1 - 3 Months

    • T

      The State University of New York

      How to Get Skilled: Introduction to Individual Skills Management (Project-Centered Course)

      Skills you'll gain: Benchmarking, Professional Development, LinkedIn, Planning, Performance Measurement, Performance Analysis, Job Analysis, Organizational Skills, Personal Development, Microsoft Excel, Self-Awareness

      4.1
      Rating, 4.1 out of 5 stars
      ·
      225 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Maryland, College Park

      Dealing With Missing Data

      Skills you'll gain: Sampling (Statistics), Statistical Programming, Data Cleansing, Data Quality, Data Analysis Software, Statistical Analysis, Statistical Methods, Statistical Modeling, R Programming, Regression Analysis, Statistical Inference

      3.8
      Rating, 3.8 out of 5 stars
      ·
      135 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Computational Thinking with Beginning C Programming

      Skills you'll gain: Computational Thinking, Data Collection, Simulations, Data Analysis, Microsoft Visual Studio, C (Programming Language), Statistical Analysis, Automation, Program Development, Data Structures, Programming Principles, Algorithms, Computer Programming, Development Environment, Descriptive Statistics, Problem Management, File Management, Distributed Computing, Debugging, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      432 reviews

      Beginner · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Use Python Regular Expressions to Process File Data

      Skills you'll gain: Test Data, Test Case, Data Validation, Verification And Validation, Scripting, Data Cleansing, Python Programming, File Management

      3.9
      Rating, 3.9 out of 5 stars
      ·
      20 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • B

      Birla Institute of Technology & Science, Pilani

      Introduction to Programming

      Skills you'll gain: Programming Principles, C (Programming Language), Computer Hardware, Computer Programming, Computer Architecture, Computational Thinking, Data Structures, Algorithms, File Management, Operating Systems, Program Development, Debugging

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      49 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      MLOps in R: Deploying machine learning models using vetiver

      Skills you'll gain: MLOps (Machine Learning Operations), Continuous Deployment, Application Deployment, Tidyverse (R Package), R Programming, Dashboard, Health Informatics, Applied Machine Learning, Continuous Monitoring, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Docker (Software), Application Programming Interface (API)

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      E

      EDUCBA

      Embedded Systems using C

      Skills you'll gain: C (Programming Language), Embedded Systems, Embedded Software, Debugging, System Programming, Microarchitecture, Computer Architecture, Data Structures, Computer Hardware, Peripheral Devices

      3.9
      Rating, 3.9 out of 5 stars
      ·
      69 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Linux Kernel Programming and Introduction to Yocto Project

      Skills you'll gain: System Programming, Linux, Embedded Systems, Debugging, Operating Systems, Peripheral Devices, Build Tools, File Systems, C (Programming Language), Development Environment, Command-Line Interface, Data Structures

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Bayesian Statistics: Mixture Models

      Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Machine Learning, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Unsupervised Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      61 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Algorithms, Data Collection, and Starting to Code

      Skills you'll gain: Computational Thinking, Data Collection, Microsoft Visual Studio, Program Development, C (Programming Language), Programming Principles, Algorithms, Development Environment, Computer Programming, Data Structures, Debugging

      4.6
      Rating, 4.6 out of 5 stars
      ·
      376 reviews

      Beginner · Course · 1 - 4 Weeks

    R learners also search

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

    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Intro to Operating Systems 2: Memory Management: Codio
    • How to Get Skilled: Introduction to Individual Skills Management (Project-Centered Course): The State University of New York
    • Dealing With Missing Data: University of Maryland, College Park
    • Computational Thinking with Beginning C Programming: University of Colorado System
    • Use Python Regular Expressions to Process File Data: Coursera Project Network
    • Introduction to Programming: Birla Institute of Technology & Science, Pilani
    • MLOps in R: Deploying machine learning models using vetiver: Coursera Project Network
    • Embedded Systems using C: EDUCBA
    • Linux Kernel Programming and Introduction to Yocto Project: University of Colorado Boulder

    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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