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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

    • 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

    • C

      Codio

      Advanced Django: Building a Blog

      Skills you'll gain: Performance Tuning, Django (Web Framework), Authentications, PostgreSQL, Object-Relational Mapping, Model View Controller, Cloud Hosting, User Accounts, Application Security, Configuration Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      111 reviews

      Advanced · Course · 1 - 4 Weeks

    • R

      Rice University

      Principles of Computing (Part 1)

      Skills you'll gain: Combinatorics, Probability, Programming Principles, Program Development, Computational Thinking, Computer Programming, Object Oriented Programming (OOP), Development Testing, Software Testing, Applied Mathematics, Debugging, Algorithms, Python Programming, Game Design, Simulations

      4.7
      Rating, 4.7 out of 5 stars
      ·
      584 reviews

      Intermediate · Course · 1 - 3 Months

    • M

      Meta

      Database Clients

      Skills you'll gain: MySQL, Django (Web Framework), Database Management, Database Application, SQL, Relational Databases, Databases, Back-End Web Development, Python Programming, Application Programming Interface (API)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      91 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Minnesota

      Introduction to Automated Analysis

      Skills you'll gain: Test Automation, Regression Testing, Software Testing, Unit Testing, Test Tools, System Testing, Code Coverage, Security Testing, Verification And Validation, Test Case, Test Data, Debugging, Automation, Functional Requirement, Application Security

      4.2
      Rating, 4.2 out of 5 stars
      ·
      82 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Accounting Data Analytics with Python

      Skills you'll gain: Jupyter, Matplotlib, Pandas (Python Package), Data Manipulation, SQL, Data Visualization Software, Seaborn, Data Processing, Data Structures, NumPy, Programming Principles, Business Analysis, Databases, Accounting, Relational Databases, Data Modeling, Python Programming, Descriptive Statistics, Statistical Machine Learning, Regression Analysis

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      106 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      Icahn School of Medicine at Mount Sinai

      Dynamical Modeling Methods for Systems Biology

      Skills you'll gain: Matlab, Mathematical Modeling, Differential Equations, Computational Logic, Applied Mathematics, Molecular Biology, Simulations, Statistical Modeling, Biochemistry, Biology, Probability, Electrical Systems

      4.7
      Rating, 4.7 out of 5 stars
      ·
      220 reviews

      Mixed · Course · 1 - 3 Months

    • E

      Epic Games

      Unreal Engine Fundamentals

      Skills you'll gain: Unreal Engine, Virtual Environment, Version Control, Video Game Development, 3D Modeling, Augmented and Virtual Reality (AR/VR), Game Design, Animation and Game Design, Multimedia, Computer Graphics, Software Installation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      53 reviews

      Beginner · Course · 1 - 3 Months

    • B

      Board Infinity

      ISTQB Foundation Level Software Testing Certification Prep

      Skills you'll gain: Test Tools, Test Planning, Configuration Management, Software Testing, Test Automation, Test Case, Integration Testing, Code Review, Software Technical Review, Software Quality Assurance, Software Development Life Cycle, System Testing, Acceptance Testing, Quality Assurance, Maintainability, Regression Testing, Unit Testing, Test Data, Functional Testing, User Acceptance Testing (UAT)

      4.3
      Rating, 4.3 out of 5 stars
      ·
      33 reviews

      Beginner · Specialization · 1 - 3 Months

    • C

      Cloudera

      Foundations for Big Data Analysis with SQL

      Skills you'll gain: Database Design, Relational Databases, Databases, SQL, Big Data, Database Systems, Operational Databases, Data Management, Virtual Machines, Data Storage, Virtualization and Virtual Machines, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Michigan

      Developing AR/VR/MR/XR Apps with WebXR, Unity & Unreal

      Skills you'll gain: Augmented and Virtual Reality (AR/VR), Augmented Reality, Virtual Reality, Unreal Engine, Unity Engine, Application Development, Prototyping, Interaction Design, User Experience Design, Human Computer Interaction, Web Development Tools

      4.6
      Rating, 4.6 out of 5 stars
      ·
      93 reviews

      Intermediate · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Foundations of Computer Science

      Skills you'll gain: Visual Basic (Programming Language), Database Management, System Software, Databases, Relational Databases, Algorithms, Computer Architecture, Network Security, Computer Hardware, SQL, Computer Science, Computer Networking, Computer Programming, Network Protocols, Programming Principles, Software Development, Automation, Analysis, Cloud Computing, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      109 reviews

      Beginner · Course · 1 - 3 Months

    R Programming learners also search

    R
    Data
    Data Analysis
    Data Science
    Data Analytics
    Beginner R Programming
    R Programming Projects
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    1…858687…288

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

    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Advanced Django: Building a Blog: Codio
    • Principles of Computing (Part 1): Rice University
    • Database Clients: Meta
    • Introduction to Automated Analysis: University of Minnesota
    • Accounting Data Analytics with Python: University of Illinois Urbana-Champaign
    • Dynamical Modeling Methods for Systems Biology: Icahn School of Medicine at Mount Sinai
    • Unreal Engine Fundamentals : Epic Games
    • ISTQB Foundation Level Software Testing Certification Prep: Board Infinity
    • Foundations for Big Data Analysis with SQL: Cloudera

    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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