Abstract¶
This notebook serves as a short reference to Python programming, numerical methods, data analysis, artificial intelligence related algorithms and visualization techniques. The content covers essential Python concepts, introduces interactive computing with Jupyter, and explores numerical approaches for solving mathematical problems. Additionally, it demonstrates how to analyze and visualize data using Python’s powerful libraries, enabling users to extract meaningful insights from both structured and unstructured datasets. The notebook emphasizes hands-on learning, providing directly executable code to facilitate understanding and application in real-world scenarios.
Introduction¶
Simulation modeling is a powerful technique used to analyze and understand complex systems by creating digital representations of real-world processes. It allows us to experiment with different scenarios, test hypotheses, and make informed decisions based on simulated outcomes. This approach is widely used in various fields, including engineering, finance, healthcare, and social sciences.
Installation¶
Besides python, we may need to install,
matplotlib: for plotting and visualization