| File Name: | System Simulation Projects with Python |
| Content Source: | https://www.udemy.com/course/system-simulation-projects-with-python |
| Genre / Category: | Programming |
| File Size : | 788.8 MB |
| Publisher: | Ralph Rothman Academy |
| Updated and Published: | September 17, 2025 |
This course is designed to teach you how to build and analyze system simulations using Python. Simulation is a powerful way to study complex systems without the cost or risk of experimenting in real life. By modeling processes such as customer arrivals, service times, machine breakdowns, or flight delays, we can test ideas, optimize resources, and understand system performance.
Throughout the course, we will focus on hands-on projects. You will simulate a bank to analyze customer waiting times and staffing needs. You will create a factory line model to study production efficiency and downtime. You will also build an airport simulation to explore queues, scheduling, and delays. Each project will be coded step by step in Python, making the learning process practical and clear.
The course starts with simple examples to explain the fundamentals of simulation and gradually moves to more detailed models. Along the way, you will learn how probability distributions are used to represent random events, how to collect performance measures, and how to interpret simulation results for decision-making.
This course is aimed at students, engineers, and professionals who want to apply simulation in areas such as operations, logistics, and manufacturing. A basic understanding of Python is enough to follow the lessons. By the end of the course, you will have the skills to design and run your own simulation models and apply them to real-world problems.
Who this course is for:
- This course is for students, engineers, and professionals who want to learn how to build and analyze system simulations using Python. It is especially useful for those interested in operations research, industrial engineering, logistics, and manufacturing. Beginners with some Python knowledge as well as practitioners looking to apply simulation to real-world projects will benefit from the lessons.
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