Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 971 MB | Duration: 3h 57m
Getting started learning R programming language and gain in demand skill in data science , statistics and mathematics.
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 Descriptions, bar graphs, etc.) in R
How to work with datasets and get statistical analysis data
No programming experience is required. You will learn everything you need to know.
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 Description, scatter Description, 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
Who this course is for
Beginner R developers who are curious about statistics, data science and mathematics.
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