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    • R Programming

    篩選依據

    ''r programming'的 321 個結果

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      Coursera Project Network

      Les Statistiques Descriptives et Inférentielles en R

      您將獲得的技能: R Programming

      4.2

      (6 條評論)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Simulation of Drum-Buffer-Rope Control Using R Simmer

      您將獲得的技能: Data Analysis, R Programming

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Two Stage Production System Optimization With R lpSolveAPI

      您將獲得的技能: Data Analysis, R Programming

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Initiation avec R Markdown

      您將獲得的技能: R Programming, Statistical Programming

      Intermediate · Guided Project · Less Than 2 Hours

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      University of Washington

      Data Science at Scale - Capstone Project

      您將獲得的技能: Business Psychology, Communication, Computer Programming, Data Analysis, Entrepreneurship, Feature Engineering, General Statistics, Leadership and Management, Probability & Statistics, Problem Solving, Python Programming, R Programming, Research and Design, Statistical Programming

      4.1

      (22 條評論)

      Mixed · Course · 1-3 Months

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      Coursera Project Network

      Simulation of CONWIP Production Control Using R Simmer

      您將獲得的技能: Data Analysis, R Programming

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Importer des Données dans R

      您將獲得的技能: R Programming

      Intermediate · Guided Project · Less Than 2 Hours

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      Codio

      Data Science and Analysis Tools - from Jupyter to R Markdown

      您將獲得的技能: Computer Programming, Python Programming, Statistical Programming, Probability & Statistics, Basic Descriptive Statistics, Data Analysis, Data Science, Data Visualization Software, Experiment, General Statistics, R Programming, Regression

      3.4

      (27 條評論)

      Beginner · Specialization · 3-6 Months

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      Università di Napoli Federico II

      Data Science con Python e R

      您將獲得的技能: Statistical Programming, Computer Programming, Python Programming, Data Management, Databases, R Programming, SQL

      4.2

      (30 條評論)

      Intermediate · Specialization · 1-3 Months

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      Queen Mary, University of London

      Master of Science in Applied Data Analytics

      獲得學位

      Degree · 1-4 Years

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      University of Colorado Boulder

      Master of Science in Data Science

      您將獲得的技能: Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Mathematics, Strategy and Operations, Computer Architecture, Databases, Leadership and Management, Communication, Hardware Design, Statistical Programming, Operating Systems, Machine Learning, Research and Design, Finance, Data Analysis, Computer Programming, SQL, Writing, Regression, Business Analysis, Data Structures, Project Management, Software Engineering, Business Communication, Probability Distribution, Entrepreneurship, Database Design, Computer Graphics, Computer Networking, Design and Product, Statistical Analysis, Statistical Tests, Accounting, Systems Design, Human Computer Interaction, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Statistical Machine Learning, Estimation, Data Visualization, Problem Solving, Operations Research, Internet Of Things, Network Architecture, Applied Mathematics, Computer Vision, Graph Theory, PostgreSQL, Deep Learning, Geometry, User Experience, Marketing, Computer Graphic Techniques, Mathematical Theory & Analysis, Programming Principles, Python Programming, Supply Chain and Logistics, Algebra, Cryptography, Business Psychology, Interactive Design, Critical Thinking, Security Engineering, Data Mining, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, User Experience Design, Cost Accounting, Differential Equations, Cloud Computing, Cyberattacks, Computer Programming Tools, Computational Logic, Scrum (Software Development), Applied Machine Learning, Calculus, Econometrics, Feature Engineering, Graphic Design, Investment Management, Other Programming Languages, Sales, Software Architecture, Software Testing, System Programming, Visual Design, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Data Warehousing, Strategy, Basic Descriptive Statistics, Budget Management, Computational Thinking, Data Analysis Software, Experiment, Exploratory Data Analysis, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Human Resources, Microarchitecture, Security Strategy, Application Development, Computer Security Models, Network Model, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Plot (Graphics), R Programming, Account Management, Banking, BlockChain, Business Process Management, C Programming Language Family, Data Architecture, FinTech, Financial Accounting, Financial Management, Geovisualization, Inventory Management, Management Accounting, Markov Model, Matlab, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Leadership Development, Network Analysis, Network Security, System Software

      獲得學位

      Degree · 1-4 Years

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      Google

      Foundations: Data, Data, Everywhere

      您將獲得的技能: Data Analysis, Data Management, SQL, Business Analysis, Data Visualization, General Statistics, Plot (Graphics), Probability & Statistics, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, Databases, Decision Making, Design and Product, Entrepreneurship, Leadership and Management, Product Design, Software Engineering

      4.8

      (73.1k 條評論)

      Beginner · Course · 1-3 Months

    與 r programming 相關的搜索

    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
    1…181920…27

    總之,這是我們最受歡迎的 r programming 門課程中的 10 門

    • Les Statistiques Descriptives et Inférentielles en R: Coursera Project Network
    • Simulation of Drum-Buffer-Rope Control Using R Simmer: Coursera Project Network
    • Two Stage Production System Optimization With R lpSolveAPI: Coursera Project Network
    • Initiation avec R Markdown: Coursera Project Network
    • Data Science at Scale - Capstone Project: University of Washington
    • Simulation of CONWIP Production Control Using R Simmer: Coursera Project Network
    • Importer des Données dans R: Coursera Project Network
    • Data Science and Analysis Tools - from Jupyter to R Markdown: Codio
    • Data Science con Python e R: Università di Napoli Federico II
    • Master of Science in Applied Data Analytics: Queen Mary, University of London

    您可以在 Data Analysis 中學到的技能

    分析 (85)
    大數據 (64)
    Python 程序設計 (47)
    商業分析 (40)
    R 語言程序設計(中文版) (37)
    統計分析 (36)
    SQL (33)
    數據模型 (29)
    數據挖掘 (27)
    探索性數據分析 (26)
    數據建模 (21)
    數據操作 (20)

    關於 R 語言程序設計(中文版) 的常見問題

    • 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.‎

    此常見問題解答內容僅供參考。建議學生多做研究,確保所追求的課程和其他證書符合他們的個人、專業和財務目標。
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