## Topic outline

### General

### Introduction to R

History behind R and some useful websites

Installing R in windows

R window to edit and execute R commands

Installation and Activation of R commander, Interface of R commander, Dataset: Activate,Editand View, Get Help on Activate Dataset, Analysis on Activated dataset

R commands and R syntax

Install and load a package in R

Save and load R file in workspace

Getting help about R commands

### Data Structures

Why Data Structures?, Types of Data Structures in R.

- Creating a matrix, Extracting elements rows or columns from a matrix, Combining two matrices, Basic matrix operations.
Creating an Array, Finding type and dimension of Array.

Creating a list, Extract a specific component from a list, Extracting a component from a sublist.

Create a factor, Unordered and Ordered factor.

Creating a Dataframe, Examining different parts of a dataframe, Edit and save a dataframe.

Importing and Exporting Data

Numerical, Nominal and Ordinal Data types, Modifying Data types.

Types of Vectors and their creation procedures, Assigning created vector into an object, Basic Vector operations , Operations between Vectors.

### Graphical Analysis

Using plot() command

Using type, pch, font, cex, lty, lwd, col arguments in plot() command.

Using main, sub, col.main, col.sub, cex.main, cex.sub, font.main, font.sub arguments in plot() command.

### Decision Tree

Introduction to Decision Tree, concepts and theory.

Follow the step by step online simulation to build a regression decision tree using CART.

Follow the step by step online simulation to build a classification decision tree using C5.

### Logistic Regression

Introduction to Logistic Regression, concepts and theory.

Follow the step by step online simulation to build a Logistic Regression model.

### Neural Network

Introduction to Neural Network, concepts and theory.

Follow the step by step online simulation to build a Neural Network Model

### Support Vector Machine

Introduction to Support Vector Machine, concepts and theory.

Follow the step by step online simulation to build a Support Vector Machine Model

### Naive Bayes

Introduction to Naive Bayes, concepts and theory.

Follow the step by step online simulation to build a Naive Bayes Model

### Clustering

Introduction to Clustering, concepts and theory.

Follow the step by step online simulation to build a Hierarchical Clustering Model

Follow the step by step online simulation to build a K-Means Clustering Model

### Association Analysis

Introduction to Association analysis, concepts and theory

Follow the step by step online simulation to build a Apriori Model

### Extras

Test your proficiency on 'Machine Learning with R'