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.
Uncertainty is an inherent challenge in digital transformation, where organizations often face unpredictable changes in technology, customer behavior, and market dynamics. Whether deciding on resource allocation, optimizing processes, or assessing risks, handling uncertainty effectively is crucial…
At this point in the course, you are able to use analytics to predict future outcomes based on historical data. Now, we will learn how to create a more sophisticated, expansive picture of possible outcomes through the use of simulation. By modeling complicated, interconnected processes, simulation…
By generating random variables from desired distributions, decision-makers can predict outcomes, optimize processes, and evaluate scenarios with precision. Whether it’s forecasting customer behavior or optimizing operational workflows, the ability to simulate random variables forms the foundation o…
Discrete event simulation is a critical tool in digital transformation, enabling organizations to analyze complex systems, manage uncertainty, and make data-driven decisions. This unit builds on foundational knowledge by applying discrete event simulation to real-world scenarios, allowing students…
Unit 6 brings together all the concepts and techniques learned throughout the course, providing students with the opportunity to develop and analyze complete simulations. The focus is twofold: building trustworthy simulations and exploring the role of simulation in prescriptive analytics. Trustwort…
The final unit of this course is a practicum that serves as a mini-capstone project, allowing you to consolidate your learning and demonstrate mastery of the tools and techniques introduced throughout the course. This project is your opportunity to apply simulation, cloud-based tools, and data scie…
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Dartmouth College is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (86/100).
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