Applied mathematics course
This course equips you with applied mathematics techniques to analyse and optimise bike-sharing operations. Delve into demand forecasting using Poisson and time-series models, queueing theory for capacity planning, linear and integer programming for fleet allocation, and simulation for policy evaluation, enabling data-backed decisions for efficient urban mobility services.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain practical skills in applied mathematics to model bike-sharing demand, optimise station capacities, and assess system performance with data-driven approaches. Master data cleaning, probabilistic modelling, daily allocation optimisation, and rebalancing policy testing to enhance service reliability in urban transport systems.
Elevify advantages
Develop skills
- Develop bike-share demand models using Poisson and time-series techniques.
- Perform capacity and queue analysis to calculate shortages and service levels.
- Optimise fleet allocation with linear and mixed-integer programming models.
- Test rebalancing policies and scenarios under peak demand conditions.
- Validate models through discrete-event simulation and stress testing.
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