Issued 6 March 2026
-Applied understanding of geospatial and spatiotemporal modelling challenges - Insight into logistics optimisation in real-world marketplaces - Knowledge of geographic pricing dynamics and market incentives - Experience translating business problems into machine learning solutions - Systems-level thinking across data, operations, and product - Improved ability to reason about trade-offs in complex, constrained environments
Having completed this session, you will be equipped with a practical understanding of how geospatial complexity manifests in real commercial systems, particularly in automotive logistics and pricing. Using Motorway as a case study, the session will explore why transporting vehicles is significantly more complex than many other logistics problems, how geographic pricing dynamics influence buyer and seller behaviour, and how machine learning can be applied to optimise decisions across space and time in a fast-moving marketplace.
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