Data Analysis with R Programming (Beginner’s Level)

The objective of this course is to extract meaningful insights from data by applying computational techniques. Transform raw data into a structured format by handling missing values, outliers, and inconsistencies. This course allows you to create your own function to perform specific task.

Target Audience:

Students who have done Bachelor of Technology (CS/IT), Bachelor of Computer Applications (BCA), Bachelor of Science in Information and Technology (B.Sc IT), Master of Computer Applications (MCA), Master of Science in Computer Science (M.Sc CS), Master of Science in Information and Technology (M.Sc IT) and professionals seeking a future in IT Industry.

Syllabus:

• Module - 1   Introduction to R Programming
• Unit 1 : Basics of R Programming
• Overview of R and its applications
• Installing R and RStudio (IDE)
• Understanding the R environment (Console, Script, Workspace)
• Unit 2 : Commands and packages of R
• Basic R commands and syntax
• Introduction to R packages and CRAN (Comprehensive R Archive Network)
• Module - 2   - Data Types and Structures in R
• Unit 1 : Basic Data Types
• Numeric, Character, Logical, Complex, and Factor
• Unit 2 : Data Structures
• Vectors, Matrices, Lists, Data Frames, Arrays
• Module - 3   Operation in R
• Unit 1 : Working with Operators
• Arithmetic Operations
• Relational and Logical Operators
• Variable Assignment and Manipulation
• Basic Functions
• Module - 4   Data Import and Export
• Unit 1 : Reading and Writing Data in different formats
• Reading Data
• Writing Data
• Module - 5   Data preprocessing techniques in R
• Unit 1 : Handling Missing Data and Transformation
• Remove Missing Values
• Data Type Conversion
• Creating New Variables
• Recoding Variables
• Handling Outliers
• Module - 6   Control structures and Loop
• Unit 1 : Conditional Statements
• if, else if, else
• Unit 2 : Loops Statements
• for loop
• while loop
• Using break and next in loops
• Module - 7   Functions in R
• Unit 1 : Working with Function
• Defining user functions in R
• Function arguments, default values, and return values
• Scope of variables in functions
• Module - 8   Practical Application of R Programming
• Unit 1 : Application
• Apply learned skill to a practical project using real world business data.