This repository contains a collection of Python scripts and Jupyter notebooks for practicing numerical methods commonly used in scientific computing and engineering applications. The exercises cover a range of topics including root finding, interpolation, differentiation, integration, linear algebra, and differential equations. Each exercise is accompanied by detailed explanations of the underlying concepts, implementation guidelines, and example use cases. Solutions are provided for reference, allowing users to compare their implementations and verify correctness. Whether you're a student learning numerical methods for the first time or a practitioner looking to refresh your skills, this repository provides a hands-on approach to mastering numerical techniques using Python.
- Exercises covering various numerical methods
- Python implementations with detailed explanations
- Jupyter notebooks for interactive learning
- Solutions provided for self-assessment
- Suitable for beginners and intermediate learners in scientific computing
- Explore the repository and enhance your understanding of numerical methods through practical exercises in Python!