Simulation for Digital Transformation

Discover how to tackle complex challenges with Simulation for Digital Transformation. Learn to use Python and SimPy to model, analyze, and optimize systems, empowering you to make data-driven decisions and lead impactful digital transformation initiatives with Dartmouth Thayer School of Engineering faculty Vikrant Vaze and Reed Harder. 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

• Address complex challenges using simulation for digital transformation
• Use Python and SimPy to develop and analyze simulation models
• Optimize systems through accurate simulation design
• Support data-driven decision making in digital initiatives

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work