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Discrete Event Simulation in Python

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Duration

4 hours

video

16 videos

Module

55 exercises

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Python’s SimPy package.

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Discover Discrete-Event Simulation
Have you ever been asked to optimize your industry or business operations? In this course on discrete-event simulation in Python, you will learn how to tackle the optimization of a myriad of processes running in parallel or in sequence.

Explore Process Optimization
Manufacturing, transportation, logistics, and supply-chain activities may require the management of several processes running in parallel or in sequence. Optimizing these processes can be a daunting task, even for small companies, but it is an essential journey needed to increase profitability, tackle bottlenecks, and improve the management of resources.

Develop Digital Twins for Real-World Processes
By leveraging Python’s SimPy package, you’ll develop digital twins for different types of industrial processes based on discrete-event simulations. You’ll encounter several real-world examples, from car production lines and eCommerce to road traffic management and supply-chain activities.

After completing this course, you will have the confidence to develop operational discrete-event models that can be used as “virtual living labs” for incrementally testing the effectiveness and cost-benefit of different management and optimization strategies.

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Discrete Event Simulation in Python
Discrete Event Simulation in Python
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