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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

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      The Structured Query Language (SQL)

      Skills you'll gain: SQL, Database Management, Query Languages, Relational Databases, Database Design, Database Theory, Data Analysis, Data Access, Data Manipulation, Data Modeling

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1K reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Introduction to R: Basic R syntax

      Skills you'll gain: R Programming, Statistical Programming, Development Environment, Programming Principles, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      46 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis

      4
      Rating, 4 out of 5 stars
      ·
      876 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      VLSI CAD Part I: Logic

      Skills you'll gain: Computational Logic, Application Specific Integrated Circuits, Theoretical Computer Science, Data Structures, Verification And Validation, Computer Architecture, Algorithms, Computer Engineering, Programming Principles, Mathematical Software, Graph Theory, Software Development Tools

      4.7
      Rating, 4.7 out of 5 stars
      ·
      553 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Introduction to Intellectual Property

      Skills you'll gain: Intellectual Property, Legal Strategy, Regulation and Legal Compliance, Business Strategy, Innovation, Case Law, Business Valuation, Economics, Policy Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Sample-based Learning Methods

      Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Regression Analysis: Simplify Complex Data Relationships

      Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Advanced Analytics, Correlation Analysis, Data Analysis, Predictive Modeling, Statistical Modeling, Supervised Learning, Variance Analysis, Machine Learning Methods, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      531 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Decentralized Finance (DeFi) Infrastructure

      Skills you'll gain: Blockchain, FinTech, Interoperability, Payment Systems, Emerging Technologies, Financial Systems, Cryptography, Market Liquidity, Financial Regulations, Digital Assets, Finance, Banking, Financial Services, Payment Processing, Derivatives, Transaction Processing, Governance

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Full-Stack Developer

      Skills you'll gain: CI/CD, GitHub, C# (Programming Language), HTML and CSS, Load Balancing, Continuous Integration, Git (Version Control System), Role-Based Access Control (RBAC), Scalability, Object Oriented Programming (OOP), Authentications, ASP.NET, Full-Stack Web Development, Web Development, Debugging, SQL, Application Deployment, Microsoft Azure, Microsoft Copilot, Graph Theory

      4.4
      Rating, 4.4 out of 5 stars
      ·
      152 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Bioinformatic Methods I

      Skills you'll gain: Bioinformatics, Molecular Biology, Biology, Data Analysis Software, Data Mining, Life Sciences, Analysis, Statistical Analysis, Databases

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      T

      The Hong Kong University of Science and Technology

      Differential Equations for Engineers

      Skills you'll gain: Differential Equations, Engineering Analysis, Applied Mathematics, Calculus, Integral Calculus, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, Linear Algebra, Vibrations, Electrical Engineering, Derivatives

      4.9
      Rating, 4.9 out of 5 stars
      ·
      2.2K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Six Sigma Tools for Improve and Control

      Skills you'll gain: Six Sigma Methodology, Process Improvement, Process Optimization, Correlation Analysis, Statistical Hypothesis Testing, Lean Six Sigma, Kaizen Methodology, Quality Improvement, Regression Analysis, Statistical Process Controls, Continuous Improvement Process, Process Capability, Quality Management, Project Management, Cost Benefit Analysis, Statistical Inference, Document Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 3 Months

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

    • The Structured Query Language (SQL): University of Colorado Boulder
    • Introduction to R: Basic R syntax: Coursera Project Network
    • Introduction to Trading, Machine Learning & GCP: Google Cloud
    • VLSI CAD Part I: Logic: University of Illinois Urbana-Champaign
    • Introduction to Intellectual Property: University of Pennsylvania
    • Sample-based Learning Methods: University of Alberta
    • Regression Analysis: Simplify Complex Data Relationships: Google
    • Decentralized Finance (DeFi) Infrastructure: Duke University
    • Microsoft Full-Stack Developer: Microsoft
    • Bioinformatic Methods I: University of Toronto

    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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