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Keep shoppingMastering the basics of Systems Modelling
45 students
Mastering the basics of Systems Modelling
A practical guide to building, analysing, and optimising discrete-event simulations
Created byDhanish Jose
Last updated 12/2025
English
What you'll learn
- xplain the fundamental concepts of discrete-event systems, including events, states, entities, resources, queues, and stochastic processes.
- Develop simulation models using standard DES modelling methodologies such as event-scheduling, process-interaction, and activity-scanning.
- Build, run, and validate discrete-event simulation models using industry-standard tools (e.g., AnyLogic, Arena, Simul8, or Python).
- Analyze simulation outputs, interpret performance metrics (such as throughput, cycle time, WIP, utilization), and use the results to support decision-making.
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Course content
5 sections • 17 lectures • 1h 56m total length
Requirements
- Basic Python programming skills, including variables, loops, functions, and working with simple libraries.
Description
Discrete Event Simulation (DES) is one of the most powerful modelling techniques used to analyse, predict, and optimise the behaviour of real-world systems. From bus networks and hospitals to factories, warehouses, call centres, and supply chains—DES helps you understand how a system behaves over time and make smarter decisions.
This beginner-friendly yet comprehensive course takes you from the fundamentals to building full simulation models step-by-step. Even if you have never done modelling or coding before, you will learn through clear explanations, guided examples, and hands-on projects.
By the end of this course, you will be able to model queues, events, processes, delays, resources, and entire systems using practical tools such as Python and SimPy. You’ll also learn how to design experiments, analyse outputs, validate your model, and interpret results like a simulation expert. Additionally, you will gain hands-on experience by developing multiple small simulations and progressing toward a complete, end-to-end project that mirrors real operational challenges. The course emphasises intuition, visualisation, and practical interpretation of results so you can confidently apply DES in academic work, industry applications, or data-driven decision-making. You will also develop a strong foundation in simulation thinking, enabling you to break down complex systems, identify bottlenecks, and evaluate alternative scenarios with clarity and confidence.
Who this course is for:
- Students, researchers, and beginners with basic Python skills who want to learn how to model and simulate real-world systems using discrete-event simulation.