Looking to future-proof your career?

It’s time to break free from stagnant salaries and costly software. Gain the expertise that will make you stand out in a crowded job market.


SAY GOODBYE TO:

Losing your job because your company trims software budgets.

Struggling to bridge the gap between your simulations and stakeholder needs.

Saying, “Let’s check if the software can handle that.”



With strong simulation skills, you can elevate your career, gaining respect (and rewards) for tackling complex challenges and driving meaningful decisions.


What is Discrete-Event Simulation?

Discrete-event simulation (DES) is a way of modelling complex systems by focusing on specific events that happen at particular points in time. Rather than tracking everything continuously, it jumps from one event to the next - like a customer joining a queue, a machine breaking down, or a shipment being dispatched. Each event changes the system in some way, and the simulation moves forward accordingly. This makes DES perfect for systems where things happen in bursts rather than steadily, such as production lines, transport networks, or service operations.

What’s great about DES is that it lets you safely experiment with “what if” scenarios. Want to see how adding another checkout lane affects waiting times or how tweaking factory layouts might speed things up? DES gives you a virtual testbed for those ideas, without the cost or risk of trying them in real life. It’s a brilliant tool for uncovering bottlenecks, optimising systems, testing scenarios and ultimately making better decisions. It is an essential tool in industries ranging from manufacturing, to healthcare, to transportation and beyond.

“If you’re considering learning simulation from Harry, you couldn’t be in better hands.”

10 Reasons Why You Should Ditch Your Off-the-Shelf Discrete-Event Simulation Software and Replace it with SimPy:

  1. Flexibility for Complex Needs: Off-the-shelf tools like AnyLogic are convenient, but they can fall short when tackling highly specialised or intricate problems. SimPy enables you to build exactly what you need, no compromises.
  2. Powerful Ecosystem Integration: Python connects seamlessly with libraries for data analysis, machine learning, and visualisation (e.g., Pandas, NumPy, Matplotlib). This allows you to combine simulations with data processing and analytics in one streamlined workflow.
  3. Cost Savings and Avoidance of Vendor Lock-In: Open-source tools like SimPy eliminate licensing fees and vendor lock-in.
  4. Transparency and Trust: Coding your own simulations makes everything transparent and easier to validate. When every detail is in the code, it’s easier to audit, reproduce results, and meet compliance requirements.
  5. Skill Development: Learning Python and building simulations sharpens your programming and problem-solving skills - useful for much more than just simulations. These skills make you versatile and better equipped for a technology-driven world.
  6. Scalability and Performance: Python simulations can scale up for distributed computing or run in the cloud. This flexibility is essential for large-scale problems or integrating results into wider data systems.
  7. Community and Collaboration: Python’s open-source community is massive, fostering innovation and support. You can learn from others, share ideas, and adapt tools to suit your needs faster than relying on proprietary software updates.
  8. Future-Proofing: Depending on a single vendor for simulation software carries risks - licensing costs can rise, or the software may not evolve with your needs. Python is open, stable, and here to stay.
  9. Deeper Understanding: Building simulations from the ground up improves your grasp of the system being modelled. This understanding often leads to better models and more insightful conclusions.
  10. Customisation of Techniques: Some challenges require unique methods or cutting-edge techniques not supported by pre-packaged software. Python lets you create these from scratch, giving you a competitive edge.

Senior Simulation Engineers Earn a Big Salary

Senior Simulation Engineers in the US earn a base salary ranging from $126k to $174k, with bonuses adding another $51k to $96k. That’s a total reward package of $177k to $270k!
Data from Glassdoor.com

“Harry consistently impressed me with his mastery of both the technical side of simulation modeling and coding as well as the nuanced aspects of simulation project management.”

Master discrete-event simulation in Python with SimPy

“Harry is simply a master of discrete-event simulation and SimPy.”

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