Learn Data Science

learn Data Science in R from Scratch

Table of Contents

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

Let’s get started !

Note: The data set used in this article is from Big Mart Sales Prediction.

1. Basics of R Programming

Why learn R ?

I don’t know if I have a solid reason to convince you, but let me share what got me started. I have no prior coding experience. Actually, I never had computer science in my subjects. I came to know that to learn data science, one must learn either R or Python as a starter. I chose the former. Here are some benefits I found after using R:

1. The style of coding is quite easy.
2. It’s open source. No need to pay any subscription charges.
3. Availability of instant access to over 7800 packages customized for various computation tasks.
4. The community support is overwhelming. There are numerous forums to help you out.
5. Get high performance computing experience ( require packages)
6. One of highly sought skill by analytics and data science companies.

There are many more benefits. But, these are the ones which have kept me going. If you think they are exciting, stick around and move to next section. And, if you aren’t convinced, you may like Complete Python Tutorial from Scratch.

More :https://www.analyticsvidhya.com/blog/2016/02/complete-tutorial-learn-data-science-scratch/