Cut logistics costs 15–30% with Python-powered route optimisation. In 8 weeks you solve TSP, CVRP, VRPTW and multi-depot routing problems using Google OR-Tools and PuLP — on real delivery networks with time windows, capacity limits, driver breaks and fleet constraints.
Supply chains run on data. The best teams use structured analytical methods — and they hire people who do too.
Each module includes live instruction, hands-on exercises with real datasets, and a graded assignment.
CVRP solved in Python step-by-step
Transport cost minimisation
Facility location + routing optimisation
Choose your capstone track and build a production-ready model you can present to management or add to your portfolio.
Inventory health check + forecast accuracy audit. No signup required.