R-Programming

Introduction to R
R as a language
Working with data in R
The R ecosystem
Why use R?
Getting started
Installation and setup
Packages
Data types
Character
Factor
Integer
Float
Date and time
Data structures
Vectors
Matrices
Lists
Data frames
Data handling
Importing data from multiple sources/formats like .csv, .txt, .xlsx, SAS and SPSS files
Exporting data to multiple formats
Handling data frames: filtering, sorting, merging
PLYR package for easy data manipulation
Functions
Commonly used built-in functions
Writing user defined functions
Installing packages
Looping functions
The “apply” family of functions
Basic visualization
Basic statistics in R
Distributions
Testing
Modeling
Graphics in R
Graphics for exploratory data analysis
Standard graphic displays
The R environment
R in the cloud
Statistical analysis with R
Linear models
Generalized linear models
Advanced statistical modeling with R
Density estimation
Survival analysis
Classification
Clustering
Introduction to Writing R Packages
Integrating with other tools.
Tableau
Python
CPP
Real-time problems.
Data manipulation with data.table package.
Interview questions.

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