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    • R Programming

    필터링 기준

    "r programming"에 대한 322개의 결과

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      Johns Hopkins University

      Data Science: Foundations using R

      획득할 기술: 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

      (47.2k개의 검토)

      Beginner · Specialization · 3-6 Months

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      Google

      Data Analysis with R Programming

      획득할 기술: Data Science, R Programming, Statistical Programming, Data Visualization, Statistical Visualization, Data Analysis, Data Analysis Software, Business Analysis, Computer Programming, Computer Programming Tools, Plot (Graphics), Statistical Analysis, Visualization (Computer Graphics)

      4.8

      (6.4k개의 검토)

      Beginner · Course · 1-3 Months

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      Johns Hopkins University

      R Programming

      획득할 기술: R Programming, Data Analysis, General Statistics, Computer Programming, Data Structures, Exploratory Data Analysis, Linear Algebra, Probability & Statistics, Probability Distribution, Statistical Programming, Statistical Tests

      4.5

      (21.9k개의 검토)

      Intermediate · Course · 1-4 Weeks

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      Duke University

      Data Analysis with R

      획득할 기술: Probability & Statistics, General Statistics, Statistical Analysis, Data 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

      (6.9k개의 검토)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Data Analytics with Excel and R

      획득할 기술: Data Analysis, R Programming, Data Visualization, Plot (Graphics), Data Management, Business Analysis, SQL, Exploratory Data Analysis, Data Mining, Data Visualization Software, Databases, Basic Descriptive Statistics, Statistical Visualization, General Statistics, Statistical Programming, Data Analysis Software, Interactive Data Visualization, Spreadsheet Software, Statistical Analysis, Big Data, Microsoft Excel, Probability & Statistics, 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

      (14.7k개의 검토)

      Beginner · Professional Certificate · 3-6 Months

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      Google

      Google Data Analytics

      획득할 기술: Data Analysis, Statistical Programming, Data Science, Business Analysis, SQL, Spreadsheet Software, Data Visualization, Business, Data Management, Data Visualization Software, R Programming, Leadership and Management, Exploratory Data Analysis, Statistical Visualization, Change Management, Strategy and Operations, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Tableau Software, Big Data, Cloud Computing, Critical Thinking, Customer Analysis, General Statistics, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget 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, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development

      4.8

      (101.3k개의 검토)

      Beginner · Professional Certificate · 3-6 Months

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      Coursera Project Network

      Getting Started with R

      획득할 기술: R Programming, Statistical Programming, Data Analysis, Data Science

      4.4

      (303개의 검토)

      Beginner · Guided Project · Less Than 2 Hours

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      Johns Hopkins University

      Data Visualization & Dashboarding with R

      획득할 기술: 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

      (292개의 검토)

      Beginner · Specialization · 3-6 Months

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      Imperial College London

      Statistical Analysis with R for Public Health

      획득할 기술: 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

      (1.7k개의 검토)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      Introduction to R Programming for Data Science

      획득할 기술: R Programming, Computational Logic, Computer Programming, Data Management, Data Science, Extract, Transform, Load, Programming Principles, Statistical Programming, Theoretical Computer Science

      4.5

      (250개의 검토)

      Beginner · Course · 1-3 Months

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      University of Colorado Boulder

      Introduction to R Programming and Tidyverse

      획득할 기술: R Programming, Statistical Programming, Business Analysis, Computer Programming, Data Analysis, Exploratory Data Analysis, Graph Theory, Mathematics, Probability & Statistics, Programming Principles

      4.1

      (17개의 검토)

      Beginner · Course · 1-4 Weeks

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      무료

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      Universidad Nacional Autónoma de México

      Introducción a Data Science: Programación Estadística con R

      획득할 기술: R Programming, Statistical Programming, Computer Programming, Mathematics, Data Analysis, Data Visualization, Linear Algebra, ArcGIS, Mathematical Theory & Analysis, Other Programming Languages, Plot (Graphics)

      4.7

      (7.8k개의 검토)

      Beginner · Course · 1-3 Months

    r programming과(와) 관련된 검색

    r programming and tidyverse capstone project
    advanced r programming
    the r programming environment
    introduction to r programming for data science
    introduction to r programming and tidyverse
    data analysis with r programming
    expressway to data science: r programming and tidyverse
    application of data analysis in business with r programming
    1234…27

    요약하자면, 여기에 가장 인기 있는 r programming 강좌 10개가 있습니다.

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

    Data Analysis에서 학습할 수 있는 스킬

    분석 (85)
    빅 데이터 (64)
    Python 프로그래밍 (47)
    비즈니스 분석 (40)
    통계 분석 (36)
    SQL (33)
    데이터 모델 (29)
    데이터 마이닝 (27)
    탐구 데이터 분석 (26)
    데이터 모델링 (21)
    데이터 조작 (20)

    R 프로그래밍에 대한 자주 묻는 질문

    • 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.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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