Skills you'll gain

There are 7 modules in this course

What you'll learn: 1. Master Discrete Event Simulation: Develop and implement event-driven simulation models in Python using tools like SimPy to analyze and optimize real-world systems. 2. Generate Random Variables: Apply techniques like the inversion and rejection methods to simulate uncertainty and model complex scenarios effectively. 3. Design Trustworthy Simulations: Learn how to validate, verify, and refine simulation models to ensure accurate and actionable decision-making results. 4. Optimize Complex Systems: Use simulation to efficiently improve workflows, allocate resources, and evaluate multi-objective solutions in diverse industries. 5. Bridge Predictive and Prescriptive Analytics: Leverage simulation as a tool to predict outcomes and recommend optimal strategies in dynamic environments.

Handling Uncertainty

Discrete Event Simulation

Simulating Random Variables with Desired Distributions

Real-world Applications of Discrete Event Simulation

Putting It All Together

Practicum

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