{"id":105103,"date":"2026-05-04T12:22:03","date_gmt":"2026-05-04T06:52:03","guid":{"rendered":"https:\/\/staging.nanoschool.in\/wp\/?post_type=product&p=105103"},"modified":"2026-06-26T14:39:54","modified_gmt":"2026-06-26T09:09:54","slug":"introduction-to-r-programming","status":"publish","type":"product","link":"https:\/\/staging.nanoschool.in\/wp\/course\/introduction-to-r-programming\/","title":{"rendered":"Introduction to R Programming"},"content":{"rendered":"
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Attribute<\/div>\n
Detail<\/div>\n
Format<\/div>\n
Online, self-paced course<\/div>\n
Level<\/div>\n
Basic \/ Beginner<\/div>\n
Duration<\/div>\n
2\u20133 Weeks<\/div>\n
Certification<\/div>\n
e-Certification<\/div>\n
Fee<\/div>\n
Free Course<\/div>\n
Tools<\/div>\n
R Programming, Data Analysis Basics<\/div>\n<\/div>\n
About the Course<\/div>\n
The Introduction to R Programming course is a free, beginner-friendly self-paced program designed to help learners understand the basics of R, a widely used programming language for data analysis, statistics, and research.<\/div>\n
The course introduces core concepts such as variables, data types, basic operations, and working with datasets in R. Learners will explore how R is used in data science, research, and analytics to analyze data and generate insights. This course is ideal for beginners who want to start programming for data-related tasks.<\/div>\n
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Program Highlights<\/div>\n
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\u2022 Free beginner-level R programming course<\/div>\n
\u2022 Online self-paced learning format<\/div>\n
\u2022 Simple explanation of programming concepts<\/div>\n
\u2022 Covers data handling and basic analysis using R<\/div>\n
\u2022 Real-world examples from research and analytics<\/div>\n
\u2022 Suitable for students and non-programmers<\/div>\n
\u2022 e-Certification upon successful completion<\/div>\n<\/div>\n<\/div>\n
Course Curriculum<\/div>\n
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Module 1: Introduction to R Programming<\/div>\n
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  • What is R Programming?<\/li>\n
  • Why R is Used in Data Science and Research<\/li>\n
  • Installing and Setting Up R<\/li>\n
  • Overview of R Environment<\/li>\n<\/ul>\n<\/div>\n
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    Module 2: Basics of R<\/div>\n
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    • Variables and Data Types<\/li>\n
    • Vectors, Lists, and Data Structures<\/li>\n
    • Basic Operators and Expressions<\/li>\n
    • Writing Simple Commands<\/li>\n<\/ul>\n<\/div>\n
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      Module 3: Working with Data in R<\/div>\n
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      • Importing and Understanding Datasets<\/li>\n
      • Basic Data Cleaning Concepts<\/li>\n
      • Exploring Data in R<\/li>\n
      • Simple Data Analysis<\/li>\n<\/ul>\n<\/div>\n
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        Module 4: Data Visualization in R<\/div>\n
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        • Introduction to Plots and Graphs<\/li>\n
        • Basic Chart Types<\/li>\n
        • Visualizing Data Patterns<\/li>\n
        • Presenting Results Clearly<\/li>\n<\/ul>\n<\/div>\n
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          Module 5: Applications and Next Steps<\/div>\n
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          • R in Data Science and Research<\/li>\n
          • Using R for Statistical Analysis<\/li>\n
          • Career Opportunities in Data and Analytics<\/li>\n
          • Mini Learning Activity \/ Concept-Based Practice<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
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            Tools, Techniques, or Platforms Covered<\/div>\n
            R Programming<\/span>
            \nData Analysis<\/span>
            \nData Visualization<\/span>
            \nBasic Statistics<\/span>
            \nDatasets<\/span><\/div>\n<\/div>\n
            Real-World Applications<\/div>\n
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            • Analyzing data for academic and research projects<\/li>\n
            • Performing basic statistical analysis<\/li>\n
            • Visualizing data using graphs and charts<\/li>\n
            • Supporting data-driven decision-making<\/li>\n
            • Preparing for advanced data science and analytics learning<\/li>\n<\/ul>\n<\/div>\n
              Who Should Attend & Prerequisites<\/div>\n
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              • This course is suitable for students, beginners, freshers, and professionals who want to learn programming for data analysis using R.<\/li>\n
              • It is also useful for learners from statistics, mathematics, research, data science, business, and non-technical backgrounds.<\/li>\n<\/ul>\n

                Prerequisites:<\/strong> No prior programming experience is required. Basic computer knowledge and interest in data and analysis are sufficient.<\/p>\n<\/div>\n

                Frequently Asked Questions<\/div>\n
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                \n
                1. Is this Introduction to R Programming course free?<\/div>\n
                Yes. This is a free online self-paced course designed for beginners.<\/div>\n<\/div>\n
                \n
                2. Do I need coding experience to learn R?<\/div>\n
                No. The course starts from basics and is suitable for non-programmers.<\/div>\n<\/div>\n
                \n
                3. What will I learn in this course?<\/div>\n
                You will learn R basics, data handling, simple analysis, and visualization concepts.<\/div>\n<\/div>\n
                \n
                4. Who can join this course?<\/div>\n
                Students, beginners, and professionals from any background can join.<\/div>\n<\/div>\n
                \n
                5. Will I receive a certificate?<\/div>\n
                Yes. Learners receive an e-Certification after completing the course.<\/div>\n<\/div>\n
                \n
                6. Is R useful for data analysis?<\/div>\n
                Yes. R is widely used for data analysis, statistics, research, visualization, and data science learning.<\/div>\n<\/div>\n
                \n
                7. Is this course suitable for non-programmers?<\/div>\n
                Yes. This course is designed for beginners and explains R programming concepts step by step.<\/div>\n<\/div>\n
                \n
                8. What is the duration of this course?<\/div>\n
                The Introduction to R Programming course is designed as a 2\u20133 week online self-paced course.<\/div>\n<\/div>\n
                \n
                9. Does this course include data visualization?<\/div>\n
                Yes. The course introduces basic plots, graphs, chart types, and ways to present data patterns clearly.<\/div>\n<\/div>\n
                \n
                10. What makes this R programming course beginner-friendly?<\/div>\n
                The course starts with R basics, explains variables, data types, simple commands, datasets, analysis, and visualization in simple language without requiring prior programming experience.<\/div>\n<\/div>\n<\/div>\n
                The Introduction to R Programming course provides a simple and structured foundation in programming for data analysis and research. It is an ideal starting point for learners who want to explore data science, statistics, and analytics using R.<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
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                This course introduces learners to the fundamentals of R Programming, including its role in data science, research, and statistical analysis. It covers basic R commands, data structures, data handling, simple analysis, visualization, and practical applications in data and analytics.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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