Published 9/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 44m | Size: 788 MB
System Simulation with Python: Build projects on banks, factories, and airports
What you’ll learn
Build discrete-event simulations in Python to model real systems such as banks, factories, and airports.
Apply probability distributions to represent random events like customer arrivals, service times, or machine breakdowns.
Analyze simulation outputs to measure performance indicators such as waiting times, resource utilization, and system capacity.
Design and code complete simulation projects step by step, from assumptions to results interpretation.
Requirements
“No advanced background is required to take this course. A basic understanding of Python syntax will help, but everything needed for simulation modeling will be explained step by step. You only need a computer with Python installed, and we will use free libraries and tools throughout the course.
Description
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.
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