R is a free, open source language used for statistical computing, Data visualization, Data manipulation and Data exploration. It’s easy to install and use. R is one of the best data Analyst tool in the market. The course is designed to give in depth knowledge with lots of practical training.

**Course Objective**

**After completion of the course student have an expertise on following areas**

- Be an expert in using R for Data manipulation, Data visualization and data exploration.
- Learn how to do programming with R
- In depth knowledge of Predictive Analytics with R.
- Complete understanding of R setup

**Who should do this course** – SAS Professionals, IT Manager, Data Analysts and Hadoop Professionals.

**Prerequisite: –** The person should have good Analytical skills, Basic programming knowledge (C, C++)

**Introduction to R Programming**

- What is R
- Role Of Analytics in Companies
- History Of R
- Features of R
- Basics Of R, R-Studio , R Markdown
- Data Types , Variable Assignment

**Obtaining and Managing R**

- Installation of R
- Packages
- Input / Output
- R Interfaces
- R Library

**Vectors**

- Analyse behaviour using vectors
- Comparing Vectors
- Selection from Vectors
- Sorting of Vectors

**Matrices**

- Work with matrices in R
- Computation with matrices
- Comparing matrices
- Selection from matrices
- Sorting of matrices

**Data Management**

- Reading Data
- Writing Data
- Reading Data files with tables
- Files connection
- Reading lines of text files

**Data Frames**

- Learn how to create data frames
- Data sets and structure
- Selection from data frames
- Sorting of data frames

**Lists**

- How to create list
- List and data structure
- Selection and sorting of list

**Reading Data from external files**

- Understanding subscripts in plots in R
- Learn how to obtain parts of vector
- Complete understanding of how to read data from external files

**Generating Plots**

- Learn how to generate plot in R
- How to generate graphs , Bar plots , Line plots
- Complete understanding of components of pie chart

**Regression in R**

- Understanding what is simple linear regression
- Understanding the various equations of Line, slope , Y-intercept regression line
- Deploying analysis using regression
- Interpreting the results

**Analyzing relationship with Regression**

- Scatter plots
- Two variable relationship
- Simple linear Regression analysis

**Advance Regression**

- Complete understanding of the measure of variation
- The concept of co-efficient of determination , F-test , the test statistic with an F-distribution
- Advanced regression in R

**Logistics Regression**

- Logistic Regression mean
- Logistic Regression in R

**Advance Logistic Regression**

- Advanced Logistic regression
- Understanding how to do prediction using logistic regression
- Understanding sensitivity and specificity
- What is ROC ( Receiver Operating Characteristics )
- ROC curve in R

**Database Connectivity with R**

- Connecting to various databases from the R environment
- Deploying the ODBC tables for reading the data
- Visualization of the performance of the algorithm using confusion matrix

**Integrating R with Hadoop**

- Creating an integrated environment for deploying R on Hadoop platform
- R Programming for MapReduce Jobs and Hadoop execution