Plan Inventory Replenishment as an MDP for an E-Commerce AI Startup
Overview
What this challenge is about.
Solve an MDP to plan inventory replenishment for an e-commerce AI startup, then benchmark your policy. Earn a verifiable certificate.
The scenario
The startup (around 35 staff, around USD 6 million ARR, sells to mid-size Indian e-commerce retailers) has seen heuristic-based inventory policies leave around 6% revenue on the table in client back-tests.
The Brief
What you'll do, and what you'll demonstrate.
Formulate and solve a single-SKU replenishment MDP and beat the current reorder-point heuristic in simulation across the 50 SKUs.
Earning criteria — what you'll demonstrate
- Translate a business problem into a well-defined MDP
- Implement value iteration and verify convergence properties
- Build a fair simulation harness on historical demand
- Communicate the limits of the model (single SKU, stationary demand)
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Mdp Modeling
Apply mdp modeling to solve real industry problems and demonstrate production-level capability.
- Value Iteration
Apply value iteration to solve real industry problems and demonstrate production-level capability.
- Dynamic Programming
Apply dynamic programming to solve real industry problems and demonstrate production-level capability.
- Simulation
Apply simulation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Policy Evaluation
Apply policy evaluation 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
Formulating a business problem as an MDP and benchmarking against the incumbent heuristic is the textbook first quarter for an applied AI scientist on an optimization team.
This challenge sharpens
- mdp-modeling
- value-iteration
- policy-evaluation
ML Researcher
Clean MDP formulations are the entry point for any RL or sequential-decision research role.
This challenge sharpens
- mdp-modeling
- dynamic-programming
- policy-evaluation
Data Scientist
Simulation-based policy comparison on historical data is core operations-research-flavored data science work.
This challenge sharpens
- simulation
- policy-evaluation
- python