R

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

 

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