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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

    • S

      Stanford University

      Probabilistic Graphical Models 3: Learning

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Markov Model, Machine Learning, Statistical Modeling, Network Analysis, Probability Distribution, Statistical Methods, Probability & Statistics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      303 reviews

      Advanced · Course · 1 - 3 Months

    • I

      IBM

      Software Developer Career Guide and Interview Preparation

      Skills you'll gain: Interviewing Skills, Professional Networking, Professional Development, Software Development, Software Engineering, Relationship Building, Programming Principles, Problem Solving, Communication Strategies, Verbal Communication Skills

      4.8
      Rating, 4.8 out of 5 stars
      ·
      259 reviews

      Beginner · Course · 1 - 4 Weeks

    • E

      EDHEC Business School

      Python and Machine Learning for Asset Management

      Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Machine Learning, Applied Machine Learning, Financial Modeling, Supervised Learning, Predictive Modeling, Risk Management, Feature Engineering, Unsupervised Learning, Regression Analysis, Statistical Methods, Dimensionality Reduction

      3.1
      Rating, 3.1 out of 5 stars
      ·
      328 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      É

      École Polytechnique Fédérale de Lausanne

      Systèmes d’Information Géographique - Partie 1

      Skills you'll gain: Geographic Information Systems, Data Modeling, GIS Software, SQL, Spatial Data Analysis, Query Languages, Relational Databases, Land Management, Global Positioning Systems, Environmental Science, Data Capture, Data Storage

      4.5
      Rating, 4.5 out of 5 stars
      ·
      283 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      NLP: Twitter Sentiment Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Cleansing, Text Mining, Scikit Learn (Machine Learning Library), Probability & Statistics, Pandas (Python Package), Natural Language Processing, Data Processing, Statistical Modeling, Data Transformation, Data Analysis, Applied Machine Learning, Supervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      366 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • E

      EDUCBA

      Introduction to AutoSAR

      Skills you'll gain: Real-Time Operating Systems, Software Development, Software Design, Software Architecture, Embedded Systems, Configuration Management, Systems Architecture, Extensible Markup Language (XML), System Configuration, Application Programming Interface (API)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      156 reviews

      Beginner · Course · 1 - 4 Weeks

    • R

      Rice University

      Python Data Visualization

      Skills you'll gain: Data Visualization Software, Plot (Graphics), Package and Software Management, Python Programming, Data Mapping, Software Installation, Scripting, Data Processing, Data Integration, Data Import/Export, Scripting Languages, Data Structures, Software Documentation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      542 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      D

      Duke University

      Programming for Python Data Science: Principles to Practice

      Skills you'll gain: Matplotlib, Pandas (Python Package), Computational Thinking, Predictive Modeling, Data Cleansing, Data Visualization Software, Visualization (Computer Graphics), Data Structures, Debugging, NumPy, Data Manipulation, Regression Analysis, Data Analysis, Python Programming, Algorithms, Simulations, Statistical Methods, Program Development, Data Science, Object Oriented Programming (OOP)

      3.8
      Rating, 3.8 out of 5 stars
      ·
      65 reviews

      Beginner · Specialization · 3 - 6 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Functional Programming in Scala Capstone

      Skills you'll gain: Scala Programming, User Interface (UI), Interactive Data Visualization, Real Time Data, Big Data, Visualization (Computer Graphics), Geospatial Mapping, Data Manipulation, Data Transformation, Spatial Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      546 reviews

      Mixed · Course · 1 - 3 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

    • 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

    • 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

    R Programming learners also search

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

    • Probabilistic Graphical Models 3: Learning: Stanford University
    • Software Developer Career Guide and Interview Preparation: IBM
    • Python and Machine Learning for Asset Management : EDHEC Business School
    • Systèmes d’Information Géographique - Partie 1: École Polytechnique Fédérale de Lausanne
    • NLP: Twitter Sentiment Analysis: Coursera Project Network
    • Introduction to AutoSAR: EDUCBA
    • Python Data Visualization: Rice University
    • Programming for Python Data Science: Principles to Practice: Duke University
    • Functional Programming in Scala Capstone: École Polytechnique Fédérale de Lausanne
    • Intro to Snowflake for Devs, Data Scientists, Data Engineers: Snowflake

    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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