R Programming

In this course enables the participants of the R Programming Course to get acquainted with the core concepts such as Basic Syntax, Data Types, Structures and Manipulate objects using R in a step-by-step manner. This course helps the learners to get equipped with important statistical computing skills that are needed for an R Programmer such as Reading Data into R, Writing R Functions, Accessing R Packages, Profiling R Code, Debugging, Organizing, and Commenting the R Code. By the end of this course, you will become well-versed with the key topics such as R Function, R Source Code, R Data Types, R Command Lines, Time-series analysis, Linear and Logistic Regression, Assignment Operators, and Survival analysis efficiently.

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In this course enables the participants of the R Programming Course to get acquainted with the core concepts such as Basic Syntax, Data Types, Structures and Manipulate objects using R in a step-by-step manner. This course helps the learners to get equipped with important statistical computing skills that are needed for an R Programmer such as Reading Data into R, Writing R Functions, Accessing R Packages, Profiling R Code, Debugging, Organizing, and Commenting the R Code. By the end of this course, you will become well-versed with the key topics such as R Function, R Source Code, R Data Types, R Command Lines, Time-series analysis, Linear and Logistic Regression, Assignment Operators, and Survival analysis efficiently.

Course content

 

Introduction to R 
  • What is R?
  • History and Features of R
  • Introduction to R Studio
  • Installing R and Environment Setup
  • Command Prompt
  • Learning R programming Syntax
  • Understanding R Script Files
R Programming basics 
  • Data types in R
  • Creating and Managing Variables
  • Understanding Operators
  • Assignment Operators
  • Arithmetic Operators
  • Relational and Logical Operators
  • Other Operators
  • Understanding and using Decision Making Statements
  • The IF Statement
  • The IF…ELSE statement
  • Switch Statement
Understanding R data structure
  • Variables in R
  • Vectors
  • Matrices
  • List
  • Data frames
  • Using Cbind, Rbind, attach and detach functions in R
Data Manipulation in R
  • Data sorting
  • Find and remove duplicates record
  • Cleaning data
  • Recoding data
  • Merging data
  • Slicing of Data
  • Merging Data
  • Apply functions
Data Import techniques in R
  • Reading Data
  • Writing Data
  • Basic SQL queries in R
  • Web Scraping
Comprehending Loops and Control 
  • Repeat Loop
  • While Loop
  • For Loop
  • Controlling Loops with Break and Next Statements
Learning more about Data Types 
  • Understanding the Vector Data type
  • Introduction to Vector Data type
  • Types of Vectors
  • Creating Vectors and Vectors with Multiple Elements
  • Accessing Vector Elements
  • Understanding Arrays in R
  • Introduction to Arrays in R
  • Creating Arrays
  • Naming the Array Rows and Columns
  • Accessing and manipulating Array Elements
 Learning the Matrices in R 
  • Introduction to Matrices in R
  • Creating Matrices
  • Accessing Elements of Matrices
  • Performing various computations using Matrices
Charts and Plots
  • Box plot
  • Histogram
  • Pie graph
  • Line chart
  • Scatter plot
Learning the List in R 
  • Understanding and Creating List
  • Naming the Elements of a List
  • Accessing the List Elements
  • Merging different Lists
  • Manipulating the List Elements
  • Converting Lists to Vectors
 Getting to know and Working with the Factors 
  • Creating Factors
  • Data frame and Factors
  • Generating Factor Levels
  • Changing the Order of Levels
 Learning Data Frames 
  • Creating Data Frames
  • Matrix Vs Data Frames
  • Subsetting data from a Data Frame
  • Manipulating Data from a Data Frame
  • Joining Columns and Rows in a Data Frame
  • Merging Data Frames
  • Converting Data Types using Various Functions
  • Checking the Data Type using Various Functions
 Functions in R 
  • Understanding Functions in R
  • Definition of a Function and its Components
  • Understanding Built-in Functions
  • Character/String Functions
  • Statistical and Numerical functions
  • Time and Date Functions
  • Understanding User Defined Functions (UDF)
  • Creating a User Defined Function
  • Calling a Function
  • Understanding Lazy Evaluation of Functions
 Functioning with External Data 
  • Understanding External Data
  • Understanding R Data Interfaces
  • Working with Text Files
  • Working with CSV Files
  • Understanding Verify and Load for Excel Files
  • Using written() and ReadBin() to manipulate Binary Files
  • Understanding the RMySQL Package to Connect and Manage MySQL Databases
Data Visualization with R 
  • What is Data Visualization
  • Understanding R Libraries for Charts and Graphs
  • Using Charts and Graphs for Data Visualizations
  • Exploring Various Chart and Graph Types
  • Pie Charts and Bar Charts
  • Box Plots and Scatter Plots
  • Histograms and Line Graphs
 Knowing about Statistical Computation using R 
  • Understanding the Basics of Statistical Analysis
  • Uses and Advantages of Statistical Analysis
  • Understanding and using Mean, Median, and Mode
  • Understanding and using Linear, Multiple and Logistic Regressions ∙ Generating Normal and Binomial Distributions
  • Understanding Inferential Statistics
  • Understanding Descriptive Statistics and Measure of Central Tendency
 Packages in R 
  • Understanding Packages
  • Installing and Loading Packages
  • Managing Packages

 

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Course Prerequisites

 
  • Basic knowledge of programming language can be helpful.

Who can attend

 
  • Software Engineers and Data Analysts
  • Business Intelligence Professionals
  • SAS Developers wanting to learn the open-source technology
  • Those aspiring for a career in Data Analytics

Number of Hours: 40hrs

Certification

Statistics with R Certification by Duke University (Coursera)

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  • Mock Interviews
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  • Materials
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  • Virtual Live Experience
  • Preparing for Certification

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