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So You Need to Learn R

 

So You Need to Learn R

GETTING STARTED
Why You Should Learn R Programming: 5 Reasons

    What is R? R is a programming language commonly used for statistical computing and graphics. ...
    #1: R is built for data science. ...
    #2: R is a great language for learning the basics. ...
    #3: R works with a wide range of packages. ...
    #4: R has a supportive developer community. ...
    #5: R is used in industry and academia. ...
    The Bottom Line.
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What you'll learn

  • How to load, manipulate, analyze, and graph data in R
  • Foundational programming concepts
  • How to approach data problems in a programming language

Requirements

  • Familiarity with basic statistics

Description

If you need to develop more advanced data skills, a programming language like R is the answer. In this course, we'll cover foundational programming concepts, and learn how to load, manipulate, analyze, and visualize data in the R language. Screen-cast lectures will walk you through the how and why of coding in R, from data types and control structures, to linear models and graphing. Carefully crafted exercises will give you practice and expand your abilities.

By the end of the course, you'll be a junior R programmer with a solid foundation of knowledge -- not just some quick tricks. You'll be able to tackle real problems, according to best practices, and present your results visually. You'll be prepared to learn more advanced techniques, including tools specific to your field or industry. And you'll start thinking about data like a programmer, opening up a whole new world of understanding.

This course assumes only high-school level algebra and some familiarity with statistics. It is appropriate for someone with limited or no prior programming experience, someone who has dabbled in R but wants a more formal introduction, or someone who has worked with other languages like Python, but wants to add R to their repertoire.


Who this course is for:

  • Scientists and researchers with limited programming experience
  • Analysts who want to add another tool to their skillset
  • Beginner R users who want a more formal introduction to the language
  • Doctoral students in a field where R is the standard for data analysis
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