Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.45 GB | Duration: 6h 28m
Learn R Programming using R and R Studio. Beginners course for Data Analysts, Data Scientists. Includes R Project.

What you'll learn
What R is and how it is used in Data Science
Data types in R, coding style, and comments
How to use Vectors in R
How to use Matrices in R, including matric operations and modification
How to use Arrays in R
About using Lists in R including how to select list elements
All about Factors in R
How to use Loops in R and IF, ELSE statements
How to use Functions in R
How to use Data Frames including tidyverse and tibbles in R

Description
In this R Programming for Beginners course, we start at the very beginning and introduce you to the R programming language. After that, we get you set up in R Studio and show you how to prepare the R Workspace.

We also show you how to import data into R Studio from various file formats before launching into the essential R components - Vectors, Matrices, Arrays, Lists, Factors, Loops, Functions, Dataframes and so much more.

This course includes downloadable challenges throughout to help you implement in real life what you are learning. At the end of the course, you pull everything you have learned together and complete a mini-project to help develop your skills.

This course is about hands-on learning, not just theory!

In this course you will learn:

What R is and how it is used in Data Science

Data types in R, coding style, and comments

How to use Vectors in R

How to use Matrices in R, including matric operations and modification

How to use Arrays in R

About using Lists in R including how to select list elements

All about Factors in R

How to use Loops in R and IF, ELSE statements

How to use Functions in R

How to use Data Frames including tidyverse and tibbles in R

To complete your first R programming assignment

This course includes:

6 hours of video tutorials

70+ individual video lectures

Exercise files to practice what you learned

An R project at the end of the course to implement what you have learned

Screenshots



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