BIG BYTE

R PROGRAMMING: FOUNDATIONS TO DATA SCIENCE & ANALYTICS

Duration: 3 Months | Course Code: RPROG | Mode: Offline / Online

This comprehensive curriculum is designed to take students from foundational programming concepts through advanced data manipulation and publication-quality data visualization. Focused heavily on practical application, the course ensures students master data handling using the R environment.

Curriculum Roadmap

Module 1: Getting Started

• R Environment: RStudio IDE setup, working with the R Console & Script Editor
• Operators & Variables: Basic Math Operators, Variables, Assignment (<-)
• Data Types: Core Data Types (Numeric, Character, Logical)

Module 2: Data Structures

• Vectors: Creating Vectors, Vectorized operations, and Subsetting rules
• Complex Collections: Lists, Matrices, and Multi-dimensional structures
• Categorical Data: Factors and Level ordering for Categorical Data
• Data Frames: Understanding, creating, filtering, and navigating 2D Data Frames

Module 3: Programming Logic

• Conditional Flow: Conditional Statements (if, else if, else)
• Logical & Comparison: Logical Operators (&, |, !), Comparison Operators
• Iterative Execution: For Loops, While Loops, and control jump statements

Module 4: Data I/O & Functions

• Import & Export: Importing external data formats (CSV, Excel), Exporting cleaned datasets
• Built-in Functions: Applying core mathematical, summary, and statistical functions
• User-Defined Functions: Writing custom modular User-Defined Functions (UDFs)

Module 5: Tidyverse Wrangling

• Tidyverse Overview: Introduction to the modern Tidyverse data science ecosystem
• The Pipe Operator: Fluent chaining workflows with the Pipe Operator (%>% or |>)
• dplyr Data Transformation: Essential verbs: filter(), select(), mutate(), arrange(), and summarise()

Module 6: Data Visualization

• Grammar of Graphics: Deep-dive into ggplot2 layering architecture
• Core Plot Types: Scatter plots, Bar charts, Histograms, Box plots, Density curves
• Aesthetics & Styling: Customizing axes, labels, color palettes, custom themes, and plot legends

Course Assessment Metrics

Who Should Enroll?

College and university students, aspiring data scientists, business intelligence professionals, researchers, economists, and anyone eager to build production-grade data analytics and visualization capabilities in R.

Career Outcomes:

• Master the R programming language and RStudio environment
• Clean, filter, and reshape messy datasets using Tidyverse & dplyr
• Generate publication-quality visualizations using ggplot2
• Portfolio-ready Capstone Project demonstrating end-to-end data analytics
• ISO 9001:2015 & Govt. Registered Certificate from BIG BYTE Computer Education

Enroll in R Programming