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R has a steep learning curve . If you are one of those who have heard the Buzz around Data Science and has thought of Learning R ,but still not been able to do much , start going through “R” learning materials on this website. Install “R” , “R Studio” and just spend some time . It takes a while before you start getting connected and start using R for the Advantage that it provides .

Contact at **info@instrovate.com** , if you are looking for an **Economical Instructor Based Online Training** For R Programming that can get you connected to the Beautiful “R” world on a consistent basis before you start Flying !!!

**Links to R Programming Learning Material on this website .**

**Start Your R Journey Today :**

- R Installation
*R Studio Installation**Getting Started with R – First Hands On**Loading Iris Data Set In R**R Packages**dplyr package in R*- Common Functionalities in R
- Operators & Missing Value in R
- Coercion in R
- Data Structure in R
- Scatter Plot in R – Using mtcars dataset
- Using ggplot2 For Data Analytics in R – Diamond Dataset
- Control Structure in R – if , else , for , while , repeat , break , next , return
- Working with Time & Date in R Programming Language
- Regular Expression & Its Usage in R
- apply() Family in R
- User Defined Functions in R
- SQL In R
- How To Import Different Formats in R
- Chi Squared Test of Independence
- Correlation in R
- Spatial Visualization Using R – Part 1
- Spatial Visualization Using R – Part 2
- “ggpubr” package in R for Data Visualization

**Course 1: R Programming Workshop**

**Pre-requisite : None**

This Course is for an **Analytics Beginner** with Little or No Programming Experience where in we go through all the R programming concepts step by step giving proper time and complete Hands on till the concept sticks .

This course creates the Foundation and is very important if you want to start your Analytical Journey and wants to do Machine learning / Statistical Computing using R in the near future.

All the time spent here really pays off as based on our personal experience in Data Science , just doing a Google Search and pasting the code in R Console can only give temporary happiness !!

- Introduction to
**R Programming** - R as a
**Calculator** - Understanding
**Vectors**through use case - Understanding
**Matrices**through use case - Understanding
**Factors**through use case - Understanding
**Data Frames**through use case - Understanding
**Lists**through use cases - Understanding
**Operators**through use case - Understanding
**Conditional Statements**through use case - Understanding
**Functions**through use case - Understanding
**Packages**through use case - Start Working on
**Dates & Time**in R - Setting up the
**Platform for****Data Science**through R Programming - Step By Step Learning of How to
**Load External Data**into R - Using skills learned above for
**Data Pre Processing**through R **Data Cleansing**Hands On- Using
**dplyr**package for**Data Manipulation**& Exploration - Inner Join / Left Join / Right Join / Full Join / Semi Join –
**Joins In R using dplyr** **Data Visualization**Overview**using ggplot2**

**Course 2 : Machine Learning With R Programming**

**Pre-requisite : Course 1 (R Programming)**

- Supervised vs Unsupervised ML
- Classification Vs Regression
- Linear Regression – Simple , Multiple in R
- Logistic Regression – Simple, Multiple in R
- Decision Trees
- Random Forest
- SVM
- Naive bayes
- K Nearest Neighbors ( KNN )
- Hierarchial Clustering
- K Means Clustering
- Market Basket Analysis