Solving Problems with Numerical Methods – R Code Repository

This repository contains R code and resources related to the course "Solving Problems with Numerical Methods" by Janani Ravi. The course provides a comprehensive introduction to the conceptual understanding and practical implementation of numerical techniques for solving mathematical problems that are difficult or impossible to solve analytically.

📚 Course Overview

Many real-world problems (such as weather prediction, spacecraft trajectory, and real-time pricing) are too complex for symbolic solutions but can be tackled using numerical methods. This course teaches a wide variety of numerical techniques and their applications using the R programming language.

Modules Covered

Understanding Numerical Methods

• Differences between numerical and analytical methods
• Importance of numerical procedures

Applying Numerical Methods to Solve Problems

• Direct and iterative techniques for solving systems of linear equations
• Interpolation and extrapolation methods

Working with Graphs Using Numerical Techniques

• Graph representation in R
• Real-world applications of graph algorithms

Implementing Local Search and Optimizations

• Local search techniques for problems like N-queens
• Stochastic local search, simulated annealing, and threshold accepting algorithms

Implementing Integration and Differentiation

• Numerical differentiation and integration using R

🧑‍💻 Repository Structure

• Each folder or script corresponds to a module or major topic from the course.
• Well-commented R scripts for each numerical method demonstrated in the course.
• Example datasets used for exercises and demonstrations.

🛠️ How to Use

1. Clone this repository:

   git clone https://github.com/Anikk1234/Solving-Problems-with-Numerical-Methods.git

2. Open the relevant R script for the topic you want to explore.
3. Run the code in Jupyter Notebook or RStudio.
4. Modify and experiment with the code to reinforce your understanding of the concepts.

🚀 Topics & Techniques Included

• Solving systems of linear equations (direct & iterative)
• Interpolation and extrapolation
• Graph representations and algorithms
• Local search, simulated annealing, and optimization
• Linear programming problem formulation and solution
• Numerical integration and differentiation

📈 Prerequisites

• Basic knowledge of R programming
• Familiarity with mathematical concepts (algebra, calculus, optimization) is helpful but not required

📦 Resources

• Course Page on Pluralsight
• R Documentation

🤝 Contributing

Feel free to fork this repo and submit pull requests if you want to add more examples or improve existing code.

📄 License

This repository is for educational use only. Please review the course provider’s terms of use and licensing for any proprietary content.

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Author: Anik Kirtania

Happy Learning & Coding!
Implement and explore numerical methods using R.