R is a programming language and software environment that can be used for graphic representation, statistical analysis, and reporting.
R is a programming language and software environment that can be used for graphic representation, statistical analysis, and reporting. This R Programming course is intended to provide a thorough understanding of R’s operation and environment setup.
Participants will learn R concepts such as variables, operators, data types, etc. During this course, you will learn how to name, access, and manipulate list elements and how to convert lists to vectors.
Participants will learn how to work with various files in R, including CSV files, Excel files, binary files, XML files, and JSON files. Delegates will be able to create boxplots and scatterplots after completing this course.
Prerequisites
There are no prerequisites to enrol in this course, but a general understanding of the programming language can benefit.
What will you gain after this course
In R, grasp the concepts of data reshaping and regression.
Discover how to name, access, and manipulate list elements.
Gain in-depth knowledge of R programming and how to set up the R environment.
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Data Science is an arena of reconstructing unstructured data to a structured model and confer it into knowledge.
It covers the most essential topics you must learn to begin programming with R. With more than two million global users, the R language is rapidly turning into a top programming language specifically in the space of data science as well as statistics.
Data analysis is crucial to accurately predict the performance of an application. The course begins by getting you started with R, including basic programming and data import, data visualization, pivoting, merging, aggregating, and joins.
This R Programming course aims to give delegates the knowledge to use effective programming principles and to write code in R. R is a powerful statistical language.
This course is aimed at those who want to incorporate R into their data analysis and business intelligence, particularly to replace existing Excel-based workflows.
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