R Programming Online Training

 >>  R Programming Online Training

R Programming Online Training


 (5) | 750 Ratings


Introduction


R Programming Online Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 25 Hrs 8 Weekends 5 Days
Hours 1hr/day 2 Hours a day 6 Hours a day
Training Mode Online Classroom Online Classroom Online Classroom
Delivery Instructor Led-Live Instructor Led-Live Instructor Led-Live


Course Curriculum

R Programming Online Training

Data Objects

Data types

  • Double
  • Integer
  • Complex
  • Logical
  • Character
  • Factor
  • Dates and Times
  • Missing data and Infinite values

Data structures

  • Vectors
  • Matrices
  • Arrays
  • Data frames
  • Time-series objects
  • List
  • The str function

Importing data

  • Text files
  • Excel files
  • Databases
  • The Foreign package

Data Manipulation

  • Vector subscripts
  • Matrix subscripts
  • Manipulating Data frames
  • Attributes
  • Character manipulation
  • Creating factors from continuous data

Writing functions

  • Introduction
  • Arguments and variables
  • Control flow
  • Debugging your R functions

Efficient calculations

  • Vectorized computations
  • The apply and outer functions
  • Using Compiled code

Graphics

  • More plot functions
  • Modifying a graph
  • Trellis Graphics
  • The ggplot2 package

Statistics

  • Basic statistical functions
  • Regression models
  • Linear regression models
  • Logistic regression
  • Tree models
  • Survival analysis
  • Non linear regression

Object Oriented Programming

R Language objects

Exam & Certification

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Course Curriculum

R Programming Online Training

Data Objects

Data types

  • Double
  • Integer
  • Complex
  • Logical
  • Character
  • Factor
  • Dates and Times
  • Missing data and Infinite values

Data structures

  • Vectors
  • Matrices
  • Arrays
  • Data frames
  • Time-series objects
  • List
  • The str function

Importing data

  • Text files
  • Excel files
  • Databases
  • The Foreign package

Data Manipulation

  • Vector subscripts
  • Matrix subscripts
  • Manipulating Data frames
  • Attributes
  • Character manipulation
  • Creating factors from continuous data

Writing functions

  • Introduction
  • Arguments and variables
  • Control flow
  • Debugging your R functions

Efficient calculations

  • Vectorized computations
  • The apply and outer functions
  • Using Compiled code

Graphics

  • More plot functions
  • Modifying a graph
  • Trellis Graphics
  • The ggplot2 package

Statistics

  • Basic statistical functions
  • Regression models
  • Linear regression models
  • Logistic regression
  • Tree models
  • Survival analysis
  • Non linear regression

Object Oriented Programming

R Language objects

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