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    R Programming Training

    BY
    Mindmajix Technologies

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    Mode

    Online

    Fees

    ₹ 9600 12000

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 9,600  ₹12,000
    certificate availability

    Yes

    certificate providing authority

    Mindmajix Technologies

    The syllabus

    Introduction to R programming

    • Installing R studio
    • Command line_Data Editor
    • Packages and Libraries
    • Define variables
    • Types of variables
    • Variable Assignment
    • What is a Data type?
    • Data types in R
    • Operators in R

    Loops and Statements

    • “While” Loop
    • “For” Loop
    • “IF” statement

    Building Blocks of R

    • Introduction to Objects 
    • Creating an Object
    • Coercion rules
    • Functions and Arguments
    • Creating a function in R

    Strings

    • Format and Print functions
    • Paste function
    • Splitting
    • Replacement and Manipulations

    Vectors

    • Introduction to vectors
    • Vector recycling
    • Creating and Naming a Vector
    • Calculating and Comparing total winning

    Matrices

    • Creating a Matrix
    • Indexing the element from a Matrix
    • Slicing a Matrix
    • Matrix Arithmetic
    • Matrix Operations
    • Lists

    Data Frames

    • Introduction to Data frames
    • Creating a Data frame
    • Data Import and Export
    • Importing a CSV
    • Slicing and Indexing a Data frame
    • Data Frame operations

    Manipulating and Visualizing the Data

    • Data Transformations with R through Dplyr package
    • Sampling Data
    • Pipe operator
    • Tidying Data - gather(), unite(), separate(), and spread()
    • Introduction to Data visualisation
    • Introduction to ggplot2
    • Building a Histogram and bar chart with ggplot2
    • Building a scatterplot through ggplot2

    Calculations

    • Sequences
    • Repeats
    • Ordering and Sorting

    Data Analysis

    • Differentiate Population and Sample
    • Skewness
    • Mean, Median, and Mode
    • Correlation and Covariance
    • Confidence Intervals and Standard Deviation
    • Hypothesis Testing
    • Type I and Type II errors
    • Test for the mean
    • P-value
    • Comparing two means
    • Linear Regression Model
    • Differentiate Regression and Correlation
    • Geometrical representation
    • Doing a Regression
    • Interpreting the Regression table
    • R-squared

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