R Programming Details

  • R Programming course overview

    R is an open source programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years. R is a GNU package R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. While R has a command line interface, there are several graphical front-ends available. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. R can also be collaborated with other data management tools like excel, access, Oracle, sql server which makes it a powerful tool.

    Syllabus

      Introduction to R

    • What is R?
    • Why R?
    • Installing R
    • R environment
    • R console and Editor

      Understanding R data structure

    • Variables in R
    • Scalars
    • Vectors
    • Arrays
    • Matrices
    • List
    • Data frames
    • Using c, Cbind,Rbind, attach and detach functions in R
    • Factors

      Importing data

    • Reading Tabular Data files
    • Reading CSV files
    • Importing data from excel
    • Importing data from XML Files
    • Importing data from JSON Files
    • Saving in R data
    • Loading R data objects
    • Writing to files
    • Accessing database

      Manipulating Data

    • Selecting rows/observations
    • Selecting columns/fields
    • Merging data
    • Relabelling the column names
    • Converting variable types
    • Data sorting
    • Data aggregation

      Using functions in R

    • Commonly used Mathematical Functions
    • Commonly used Summary Functions
    • Commonly used String Functions
    • User defined functions
    • local and global variable

      R Programming Control Structure and Operators

    • While loop
    • If
    • For loop
    • Arithmetic operations

      Charts and Plots

    • Box plot
    • Histogram
    • Pareto charts
    • Pie graph
    • Line chart
    • Scatterplot
    • Developing graphs

      R Programming Statistics

    • Mean, Median & Mode
    • Regression
    • Distribution
    • Analysis of Covariance
    • Time Series Analysis
    • Nonlinear Least Square
    • Decision Tree
    • Chi Square Tests

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    Training Methodology

    40 Hrs of Class Room Training

    Study Material

    4 Assignments

    1 Project[10hrs]

    Online Tests

    Final Online Test

    Certification

    Life Time Access of Training Resources

    Training Fee: 8000 Early bird fee 5000
    Discount Policy

    Group Discount : 4 and above 15% discount

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