applied mathematics course
This course equips learners with applied mathematical techniques to optimize bike-sharing systems through demand modeling, capacity planning, optimization, and simulation.

from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
This Applied Mathematics Course provides practical tools to model bike-sharing demand, size station capacity, and evaluate performance using clear, data-driven methods. You will learn to clean and preprocess open datasets, build probabilistic demand models, set up daily allocation optimization, and test simple rebalancing policies so you can quantify service levels and improve real-world system reliability.
Elevify advantages
Develop skills
- Bike-share demand modelling: build Poisson and time-series models quickly.
- Capacity and queue analysis: compute shortages, overflows, and service.
- Optimisation for fleets: set up LP and MIP models for daily bike allocation.
- Scenario and policy testing: evaluate rebalancing rules under rush-hour demand.
- Simulation and validation: stress-test models with discrete-event experiments.
Suggested summary
Before starting, you can change the chapters and 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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