What is 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.

Why learn R programming?

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.

What are typical careers that use R programming?

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.

How can online courses help me learn R programming?

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.

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''r programming'的 323 個結果

Johns Hopkins University
Data Science: Foundations using R
您將獲得的技能： R Programming, Data Analysis, Data Science, Exploratory Data Analysis, Statistical Programming, Data Visualization Software, Software Visualization, Statistical Visualization, Basic Descriptive Statistics, General Statistics, Big Data, Computer Programming, Computer Programming Tools, Data Structures, Experiment, Linear Algebra, Machine Learning Software, Probability & Statistics, Probability Distribution, Software Engineering Tools, Spreadsheet Software, Statistical Tests, Application Development, Business Analysis, Data Management, Data Visualization, Extract, Transform, Load, Knitr, Plot (Graphics)
4.6
（47.2k 條評論）
Beginner · Specialization · 3-6 Months
Duke University
Data Analysis with R
您將獲得的技能： Probability & Statistics, General Statistics, Data Analysis, Statistical Analysis, Regression, R Programming, Statistical Programming, Statistical Tests, Bayesian Statistics, Econometrics, Business Analysis, Data Science, Probability Distribution, Mathematics, Correlation And Dependence, Experiment, Exploratory Data Analysis, Machine Learning, Machine Learning Algorithms, Basic Descriptive Statistics, Data Mining, Plot (Graphics), Statistical Visualization, Data Analysis Software, Data Visualization
4.7
（6.9k 條評論）
Beginner · Specialization · 3-6 Months
Google
Google Data Analytics
您將獲得的技能： Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Change Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
（102.2k 條評論）
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analytics with Excel and R
您將獲得的技能： Data Analysis, R Programming, Data Visualization, Plot (Graphics), Data Management, SQL, Exploratory Data Analysis, Data Mining, Databases, Basic Descriptive Statistics, General Statistics, Data Visualization Software, Statistical Programming, Data Analysis Software, Interactive Data Visualization, Statistical Visualization, Statistical Analysis, Big Data, Microsoft Excel, Probability & Statistics, Business Analysis, Spreadsheet Software, Database Theory, Regression, Statistical Tests, Data Science, Data Structures, Software Visualization, Machine Learning, User Experience, Probability Distribution, NoSQL, Python Programming, Applied Machine Learning, Deep Learning, Estimation, Geovisualization, Linear Algebra, Machine Learning Algorithms, Machine Learning Software, SAS (Software), Spatial Data Analysis, Statistical Machine Learning, Cloud Computing, Data Architecture, Data Model, Data Warehousing, Database Administration, Database Application, Database Design, Mathematics, Visualization (Computer Graphics), Advertising, Apache, Communication, Computational Logic, Computer Programming, Extract, Transform, Load, Leadership and Management, Marketing, Operating Systems, Professional Development, Programming Principles, System Programming, Theoretical Computer Science
4.7
（14.9k 條評論）
Beginner · Professional Certificate · 3-6 Months
Imperial College London
Statistical Analysis with R for Public Health
您將獲得的技能： Probability & Statistics, General Statistics, Regression, Business Analysis, Statistical Analysis, Data Analysis, Machine Learning, Machine Learning Algorithms, Statistical Programming, Mathematics, Statistical Tests, R Programming, Probability Distribution, Correlation And Dependence, Basic Descriptive Statistics, Econometrics, Estimation, Bayesian Statistics, Exploratory Data Analysis, Critical Thinking, Data Analysis Software, Forecasting
4.7
（1.7k 條評論）
Beginner · Specialization · 3-6 Months
Johns Hopkins University
Data Visualization & Dashboarding with R
您將獲得的技能： R Programming, Statistical Programming, Computer Programming Tools, Data Management, Data Visualization, Plot (Graphics), Communication, Computer Graphics, Computer Programming, Data Analysis, Geovisualization, Human Computer Interaction, Interactive Data Visualization, Interactive Design, Programming Principles, Project Management, Spatial Analysis, Statistical Visualization, Strategy and Operations
4.8
（294 條評論）
Beginner · Specialization · 3-6 Months

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總之，這是我們最受歡迎的 r programming 門課程中的 10 門

Data Science: Foundations using R: Johns Hopkins University
Data Analysis with R Programming: Google
R Programming: Johns Hopkins University
Data Analysis with R: Duke University
Google Data Analytics: Google
IBM Data Analytics with Excel and R: IBM Skills Network
Getting Started with R: Coursera Project Network
Statistical Analysis with R for Public Health: Imperial College London
Data Visualization & Dashboarding with R: Johns Hopkins University
Introduction to R Programming for Data Science: IBM Skills Network

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關於 R 語言程序設計（中文版）的常見問題

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.‎