R Programming 101: A Four-Module Introductory Training Program

This repository provides a comprehensive four-module training program for beginners to learn the fundamentals of R programming. It covers essential topics and practical techniques for data manipulation, analysis, and visualization in R. This program is designed to build foundational skills and help users confidently apply R to a variety of data science tasks.

Modules Overview:

1. Data Structures: Introduction to fundamental data structures in R, such as vectors, matrices, lists, and data frames. Learn how to create, manipulate, and use these structures effectively in your data analysis workflows.

2. Vector Operations and Loops: Understand the basics of vectorized operations, an essential concept in R programming that enables efficient data manipulation. Learn to implement control flow structures, such as for loops and while loops, to perform repetitive tasks and automate analyses.

3. Reading Data and Data Wrangling with dplyr: Learn how to import data from various sources, including Excel files and databases, into R. Gain hands-on experience with the dplyr package for data wrangling, including filtering, selecting, mutating, summarizing, and joining data to prepare it for analysis.

4. Data Visualization with ggplot2: Discover the principles of data visualization and learn to create compelling plots using the ggplot2 package. Learn how to read data from tables and transform it into meaningful visual representations to effectively communicate insights.

Who Is This For?

• Beginners: Ideal for anyone new to R programming and data science, providing a structured, easy-to-follow learning path.
• Data Enthusiasts: Suitable for anyone interested in learning how to manipulate, analyze, and visualize data using R.
• Students and Professionals: Perfect for students and professionals looking to enhance their data analysis skills with R.

Getting Started:

1. Clone the Repository:

   git clone https://github.com/mdomarsaleem/r-programming-101.git
   cd r-programming-101

2. Follow the Modules:

   • Start with the first module and progress through each to build a solid foundation in R programming.
   • Explore the provided examples and practice exercises to reinforce your learning.

Contributions and Feedback:

Contributions are welcome! Feel free to open issues for suggestions or improvements and submit pull requests to enhance the content or add new examples.