
Learn to build system simulations with SimPy in Python, modeling car washes, cafes, hospitals, and factories, managing queues and resources like servers and staff to run experiments and answer questions.
Demonstrate why this system simulation course with SimPy teaches by sharing working code on screen while students type it themselves, prioritizing hands-on practice over file handouts to build true understanding.
Explore an emergency room simulation model that manages patient flow and triage. Compare scenarios with fast track and resource constraints to optimize wait times and total time in the ER.
simulate airport operations with simpy to model aircraft lifecycles, runway clearance, and landing and takeoff queues, including emergencies, cargo scheduling, and time-based allocation for scenario comparisons.
Explore a coffee shop simulation with SimPy in Python, modeling customer arrivals, order types, prep times, and staff resources to analyze wait times and efficiency.
simulate real world systems with Python and the SimPy library through a car wash project that explores queuing, resources, and data-driven metrics to optimize wait times and lane utilization.
Model real world traffic dynamics across multiple intersections with adaptive green light durations, queue management, and priority vehicles in a SimPy-based traffic simulation.
Explore a drive-through restaurant simulation using Python and SimPy to model ordering, payment, and pickup, analyze wait times and bottlenecks, and assess resource adjustments to improve throughput.
This course is designed for anyone who wants to learn system simulation using Python’s SimPy library in a practical way. Instead of spending hours on theory, we will focus on building working projects that show how real systems behave under different conditions.
Throughout the course, we will create models of everyday systems such as a car wash, a café, and a hospital. We will also extend our work into factory-style systems where machines, resources, and workers interact. Each project introduces new parts of SimPy, so by the time you finish, you will have seen a wide range of applications.
You will learn how to model queues, resources, and random events. You will also practice running experiments to answer questions like: what happens when the system gets busier, what if we add more servers, or what if we reduce staff? These are the kinds of problems simulation helps us explore.
The course is beginner-friendly. If you know the basics of Python, you will be able to follow along. I recommend typing the code yourself and trying small changes, as this will give you real confidence with the library.
By the end, you will be ready to set up your own simulations, test ideas, and use SimPy as a practical tool for system analysis.