1. Congratulations!
Congratulations! You've reached the final video of this course.
Let's briefly review what you've learned.
2. Chapter 1: Introduction to dynamic systems and discrete-event simulation models
In Chapter 1, you learned to identify dynamic systems and recognize when discrete-event models can be used to optimize them. You learned that discrete-event models are specially designed to simulate sequences of processes typical of manufacturing, transportation, logistics, and supply chain activities. You also built your first discrete-event model using standard Python.
3. Chapter 2: Developing discrete-event models using SimPy.
In Chapter 2, you learned how to use SimPy, which is a Python package for discrete-event simulations. You learned that it involves creating a SimPy environment, adding processes and resources, and running it.
4. Chapter 3: Mixing determinism and non-determinism in models
In Chapter 3, you learned how to include deterministic and non-deterministic processes in models. Non-deterministic processes are common and need to be represented in models for an accurate representation of reality. One such example is the breaking of machines in a manufacturing process.
5. Chapter 4: Model application, clustering, optimization, and modularity
In Chapter 4, the final chapter of this course, you learned how to perform simulation ensembles based on Monte Carlo sampling to examine model uncertainty. You also learned how to perform clustering analysis of model results and use objective functions to set targets for your system optimization. Finally, you learned how to make your model modular for stable and controlled development.
6. Other DataCamp courses
You'll find your new discrete-event modeling skills valuable in your own projects dealing with process optimization, and there are other DataCamp courses that explore related topics.
7. Congratulations!
Thank you for the time you've dedicated to this course.
I find these methods and tools indispensable for my work as a modeler, and I hope you'll get the same value for your work. It has been a pleasure working with you, and I wish you the best of luck in your learning journey.