Learn R programming from scratch (step by step)

Getting started learning R programming language and gain in demand skill in data science , statistics and mathematics.

In this course you are going to learn the basics of R programming language from scratch. You don’t need prior experience in programming because everything will be explained. Of course prior experience to programming will bring added advantage for easier understanding of the concepts presented to this course.

What you’ll learn

  • How to write R code.
  • How to work with data structures (e.g vectors,matrices etc.).
  • How to use analysis graphics (scatter plots, bar graphs, etc.) in R.
  • How to work with datasets and get statistical analysis data.

Course Content

  • Course Intro Lectures –> 5 lectures • 13min.
  • R Language Syntax –> 11 lectures • 1hr 7min.
  • R Data Structures –> 12 lectures • 1hr 25min.
  • (Data analysis)Graphics in R –> 7 lectures • 55min.
  • Statistical analysis with R –> 3 lectures • 18min.

Learn R programming from scratch (step by step)

Requirements

In this course you are going to learn the basics of R programming language from scratch. You don’t need prior experience in programming because everything will be explained. Of course prior experience to programming will bring added advantage for easier understanding of the concepts presented to this course.

 

R language is usually used in statistical computing and graphical presentation to visualize and analyze data. Besides of being a demand skill in research, statistics and many more, learning R programming language have the following benefits:

  • It provides many statistical techniques (such as statistical tests, classification, clustering and data reduction)
  • It is a great resource for data analysis, data visualization, data science and machine learning
  • It is easy to draw graphs in R, like pie charts, histograms, box plot, scatter plot, etc.
  • It is a cross platform language, working on different operating system such as Windows, Mac, and Linux.
  • It is open-source and free, no need to worry about subscription fees which are common in many advanced statistical analyses tools.
  • If you face problem whilst working with the R programming language, you don’t have to worry because R has a large community support. This helps in funding solutions easier.
  • It has many packages (libraries of functions) that can be used to solve different problems.
  • Relates to other programming languages.
  • Most advanced statistical language
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