R Programming Training

BY
Mindmajix Technologies

Mode

Online

Fees

₹ 9600 12000

Important Dates

04 Feb, 2025

Course Commencement Date

08 Feb, 2025

Course Commencement Date

11 Feb, 2025

Course Commencement Date

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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