This article on a complete tutorial to learn Data Science in R from scratch, was posted by Manish Saraswat. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.

R is a powerful language used widely for data analysis and statistical computing. It was developed in early 90s. Since then, endless efforts have been made to improve R’s user interface. The journey of R language from a rudimentary text editor to interactive R Studio and more recently Jupyter Notebooks has engaged many data science communities across the world.

What you can find in this article :

1 Basics of R Programming for Data Science

Why learn R ?

How to install R / R Studio ?

How to install R packages ?

Basic computations in R

2 Essentials of R Programming

Data Types and Objects in R

Control Structures (Functions) in R

Useful R Packages

3 Exploratory Data Analysis in R

Basic Graphs

Treating Missing values

Working with Continuous and Categorical Variables

4 Data Manipulation in R

Feature Engineering

Label Encoding / One Hot Encoding

5 Predictive Modeling using Machine Learning in R

Linear Regression

Decision Tree

Random Forest

You can find the full article here. For other articles about R, click here.

## A Complete Tutorial to learn Data Science in R from Scratch

by Emmanuelle Rieuf

Jun 2, 2016

This article on a complete tutorial to learn Data Science in R from scratch, was posted by Manish Saraswat. Manish who works in marketing and Data Science at Analytics Vidhya believes that education can change this world. R, Data Science and Machine Learning keep him busy.

R is a powerful language used widely for data analysis and statistical computing. It was developed in early 90s. Since then, endless efforts have been made to improve R’s user interface. The journey of R language from a rudimentary text editor to interactive R Studio and more recently Jupyter Notebooks has engaged many data science communities across the world.

What you can find in this article :

1 Basics of R Programming for Data Science

2 Essentials of R Programming

3 Exploratory Data Analysis in R

4 Data Manipulation in R

5 Predictive Modeling using Machine Learning in R

You can find the full article here. For other articles about R, click here.

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