Get in Touch
 Duration 14 hours

Course Outline

Day One: Fundamental R Language Concepts

  • Course Overview
  • Foundations of Data Science
    • Definition of Data Science
    • Methodologies in Data Science Practice
  • Overview of the R Programming Environment
  • Variables and Data Types
  • Control Flow (Iteration and Conditional Logic)
  • R Data Structures: Scalars, Vectors, and Matrices
    • Construction of R Vectors
    • Matrix Operations
  • String and Text Processing
    • Character Data Types
    • Input/Output Operations
  • Lists
  • Functionality in R
    • Function Definitions
    • Closures
    • Application of lapply and sapply
  • DataFrames
  • Practical Exercises for All Modules

Day Two: Advanced R Programming

  • DataFrames and File Handling
  • Data Ingestion from External Files
  • Data Preparation Techniques
  • Utilizing Built-in Datasets
  • Data Visualization
    • Base Graphics Package
    • Plotting Functions: plot(), barplot(), hist(), boxplot(), and scatter plots
    • Heat Maps
    • ggplot2 Package (qplot(), ggplot())
  • Data Exploration Using Dplyr
  • Practical Exercises for All Modules

Requirements

  • Prior programming experience is recommended

Target Audience

  • Data analysts

Number of participants


Price per participant

Testimonials (3)

Upcoming Courses

Related Categories