applied mathematics course
This course applies mathematical modeling and optimization to enhance bike-sharing system efficiency, covering demand prediction, capacity analysis, fleet allocation, rebalancing strategies, and performance simulation using real-world data.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with practical mathematical tools to model demand for bike-sharing services, determine station capacities, and assess system performance through data-driven approaches. You will gain skills in cleaning and preparing open datasets, developing probabilistic models for demand, optimizing daily bike allocations, and evaluating basic rebalancing strategies to measure service quality and enhance the reliability of urban transport systems.
Elevify advantages
Develop skills
- Develop models for bike-sharing demand using Poisson and time-series methods efficiently.
- Analyze capacities and queues to calculate shortages, overflows, and service levels.
- Apply optimization techniques for fleet management, including linear and mixed-integer programming for daily allocations.
- Test scenarios and policies by assessing rebalancing strategies during peak demand periods.
- Conduct simulations and validations through discrete-event experiments to rigorously test models.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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