Simulate Hospital Bed Allocation for a Healthtech Decision Support Pilot
Overview
What this challenge is about.
Simulate hospital bed allocation with a discrete-event simulator, compare three policies, and earn a verifiable certificate.
The scenario
The healthtech (around 70 staff, NHS-focused, two trust contracts live) faces strict patient-safety requirements; the operations director will not approve a policy without simulation evidence.
The Brief
What you'll do, and what you'll demonstrate.
Recommend a bed-allocation policy with explicit uncertainty bounds, backed by a discrete-event simulation of 12 months of admissions data.
Earning criteria — what you'll demonstrate
- Build discrete-event simulators that match operational data
- Compare allocation policies under stochastic conditions
- Express uncertainty in policy recommendations honestly
- Communicate simulation results to a non-technical operations audience
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Decision Support Systems and Decision Analysis
Master · Applied Ai
Strong alignment
This challenge maps to Decision Support Systems and Decision Analysis at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Discrete Event Simulation
Apply discrete event simulation to solve real industry problems and demonstrate production-level capability.
- Simpy
Apply simpy to solve real industry problems and demonstrate production-level capability.
- Policy Comparison
Apply policy comparison to solve real industry problems and demonstrate production-level capability.
- Uncertainty Quantification
Apply uncertainty quantification to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Decision Support Systems
Apply decision support systems to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Applied AI Scientist
Simulation-based decision support for operations leaders is the bread and butter of applied AI scientists in healthcare and logistics.
This challenge sharpens
- discrete-event-simulation
- policy-comparison
- uncertainty-quantification
Data Scientist
Building credible simulators and writing operations-grade memos is exactly the kind of analytical work data scientists own in healthtech.
This challenge sharpens
- simpy
- policy-comparison
- python
AI Solutions Architect
Scoping decision-support pilots with simulation evidence is a recurring solutions-architect responsibility in regulated industries.
This challenge sharpens
- decision-support-systems
- policy-comparison
- uncertainty-quantification