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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 California, Santa Cruz

      C++ For C Programmers, Part B

      Skills you'll gain: C++ (Programming Language), Software Design Patterns, Object Oriented Programming (OOP), Computer Programming, C (Programming Language), Debugging, Algorithms, Graph Theory, Artificial Intelligence, Data Structures, Game Design

      4.5
      Rating, 4.5 out of 5 stars
      ·
      327 reviews

      Intermediate · Course · 1 - 3 Months

    • 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

      Ingeniero en base de datos de Meta

      Skills you'll gain: MySQL, MySQL Workbench, Database Management, Relational Databases, Data Modeling, SQL, Database Design, Version Control, Data Warehousing, Database Management Systems, Database Theory, Unix Commands, Extract, Transform, Load, Databases, Git (Version Control System), Django (Web Framework), Algorithms, Test Driven Development (TDD), Unit Testing, Pseudocode

      4.8
      Rating, 4.8 out of 5 stars
      ·
      312 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • 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
      Free
      P

      Peking University

      操作系统原理(Operating Systems)

      Skills you'll gain: File Systems, Operating Systems, OS Process Management, Computer Systems, System Programming, Unix, Linux, Algorithms, Virtualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      363 reviews

      Intermediate · Course · 3 - 6 Months

    • S

      Snowflake

      Intro to Snowflake for Devs, Data Scientists, Data Engineers

      Skills you'll gain: Data Manipulation, Data Lakes, Data Warehousing, SQL, Data Pipelines, Cloud Applications, Extract, Transform, Load, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Stored Procedure, Generative AI, Large Language Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      77 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Packt

      The Complete Quantum Computing Course for Beginners

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Data Structures, Data Manipulation, Computer Programming, Applied Mathematics, Algorithms, Mathematics and Mathematical Modeling, Data Processing, Scripting, Linear Algebra, Probability, Mathematical Modeling, IBM Cloud, Computer Science, Algebra, Software Installation, Probability & Statistics, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML)

      4.1
      Rating, 4.1 out of 5 stars
      ·
      26 reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Natural Language Processing on Google Cloud

      Skills you'll gain: Natural Language Processing, Large Language Modeling, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Cloud API, Cloud Solutions, Feature Engineering, Application Programming Interface (API)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      534 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Minnesota

      Introduction to Recommender Systems: Non-Personalized and Content-Based

      Skills you'll gain: Taxonomy, AI Personalization, Spreadsheet Software, Machine Learning, Predictive Analytics, Statistical Methods, Persona Development, Descriptive Statistics, Data Collection, Algorithms, Java Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      647 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Fake News Detection with Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Deep Learning, Text Mining, Artificial Neural Networks, Matplotlib, Data Cleansing, Data Import/Export, Data Analysis, Natural Language Processing, Data Processing, Data Manipulation, Machine Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      257 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Michigan

      Exploring C

      Skills you'll gain: C (Programming Language), Python Programming, Programming Principles, System Programming, Computer Programming, Unix, Computer Science

      4.5
      Rating, 4.5 out of 5 stars
      ·
      65 reviews

      Intermediate · Course · 1 - 3 Months

    • L

      LearnQuest

      Combining Scrum with Other Agile Methodologies

      Skills you'll gain: Behavior-Driven Development, DevSecOps, Test Driven Development (TDD), Kanban Principles, DevOps, Agile Software Development, Continuous Integration, Lean Methodologies, Agile Methodology, Scrum (Software Development), Continuous Deployment, Cross-Functional Collaboration, Workflow Management, Virtualization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      499 reviews

      Beginner · Course · 1 - 4 Weeks

    R Programming learners also search

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    Data Analysis
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    Beginner R Programming
    R Programming Projects
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    In summary, here are 10 of our most popular r programming courses

    • C++ For C Programmers, Part B: University of California, Santa Cruz
    • Principles of Computing (Part 1): Rice University
    • Ingeniero en base de datos de Meta: Meta
    • Practical Predictive Analytics: Models and Methods: University of Washington
    • 操作系统原理(Operating Systems): Peking University
    • Intro to Snowflake for Devs, Data Scientists, Data Engineers: Snowflake
    • The Complete Quantum Computing Course for Beginners: Packt
    • Natural Language Processing on Google Cloud: Google Cloud
    • Introduction to Recommender Systems: Non-Personalized and Content-Based: University of Minnesota
    • Fake News Detection with Machine Learning: Coursera Project 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 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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