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.

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