What is R? And Why R?-Different “flavors” of R-Installing R Studio DesktopUnderstanding R Studio-Installing Packages and Libraries in R Studio-Setting Your Work Directory.

Data Variables-Data Types – Operators – Keywords – ExceptionsFunctions

Vectors and Lists – Strings and Matrices – Arrays and Factors – Data Frames – Packages.

R- CSV files Read and Write and analyze the data – R- Excel files Read and Write and analyze the data

Introduction to Visualisation – Line Plots and Bar Charts – Pie Chart and Histogram – Scatter Plots and Parallel Coordinates – Advanced Plotting – Exporting Plots and Other Plotting Packages

Linear Regression Analysis – Formulation of Regression Model – Bivariate Regression – Statistics Associated with Bivariate Regression Analysis – Conducting Bivariate Regression Analysis – Multiple Regressions – Conducting Multiple Regression – Mapping Bivariate Regression with Real Time Example.

Logistic Function – Single Predictor Model – Determine Logistic Cut off – Estimated Equation for Logistic Regression

Factor Analysis Introduction – Factor Analysis Model – Statistics associated with Factor Analysis – Conducting Factor Analysis – Construction of Factor Analysis – Factor Analysis Method – Principal Component Analysis – Rotation Method – Mapping Factor Analysis with Real Time Example

Cluster Analysis Introduction – Statistics associated with Cluster Analysis – Conducting Cluster Analysis – Classification of Clustering Procedure – Hierarchical Clustering – Non Hierarchical Clustering

Association Rule Introduction – Apriori Algorithm – Multiple Association Rules – Market Basket Analysis (MBA) – Application of Apriori Algorithm and Market Basket Analysis

Naïve Bayes Introduction – Probabilistic Basics and Probabilistic Classification – Characteristics of Naïve Bayes – Real Time Case study using Naïve Bayes – Advantage and Shortcoming of Naïve Bayes

K – Nearest Neighbour Introduction – K – Nearest Neighbour Algorithm – Pre-Processing your dataset for KNN – How to measure “Nearby” – Choosing “K” and High “K” vs. Low “K” – Real Time case study using KNN – Advantage and Disadvantage of KNN

What is a Decision Tree? – How to create Decision Tree – Choosing and Identifying attributes for Decision Tree – Entropy and Information Gain with Intuitions – Pruning Trees and its types – Forward Pruning and Backward Pruning – Sub tree Replacement and Raising – Real time case study with Decision Tree

Ensample of Decision Tree.

Linear SVM using Hyperplane – Non-Linear Hyperplane using Kernal Trick and Advantage and Disadvantage of SVM

RFM Segmentation and Analysis – Propensity Modelling and its application – Churn Modelling using Operational Analytics – Fundamentals and Modelling Framework – Industry application – Market Basket Analysis using Marketing Analytics – Fundamentals and Analysis Framework – Industry Application – Price and In store Promotion using Retail Analytics – Price Elasticity and Optimization – Promotion Effectives using Analytics