Introduction to R:
What is R?
Why R?
Installing R
R environment
How to get help in R
R Studio Overview
Understanding R data structure:
Variables in R
Scalars
Vectors
Matrices
List
Data frames
Cbind,Rbind, attach and detach functions in R
Factors
Getting a subset of Data
Missing values
Converting between vector types
Importing data:
Reading Tabular Data files
Reading CSV files
Importing data from excel
Loading and storing data with clipboard
Accessing database
Saving in R data
Loading R data objects
Writing data to file
Writing text and output from analyses to file
Manipulating Data:
Selecting rows/observations
Rounding Number
Creating string from variable
Search and Replace a string or Number
Selecting columns/fields
Merging data
Relabeling the column names
Data sorting
Data aggregation
Finding and removing duplicate records
Using functions in R:
Apply Function Family
Commonly used Mathematical Functions
Commonly used Summary Functions
Commonly used String Functions
User defined functions
local and global variable
Working with dates
R Programming:
While loop
If loop
For loop
Arithmetic operations
Charts and Plots:
Box plot
Histogram
Pie graph
Line chart
Scatterplot
Developing graphs
Cover all the current trending packages for Graphs
Machine Learning Algorithm:
Sentiment analysis with Machine learning
C 5.0
Support vector Machines
K Means
Random Forest
Naïve Bayes algorithm
Statistics:
Correlation
Linear Regression
Non Linear Regression
Predictive time series forecasting
K means clustering
P value
Find outlier
Neural Network
Error Measure
Leading Topics:
Overture of R Shiny
What is Hadoop
Integration of Hadoop in R
Data Mining using R
Clinical research preface in R
API in R (Twitter and Facebook)
Word Cloud in R