applied mathematics course
This course equips learners with essential mathematical techniques for optimizing bike-sharing systems, covering demand modeling, capacity planning, optimization, and performance evaluation through practical, data-driven methods.

flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This Applied Mathematics Course provides practical tools to model bike-sharing demand, determine station capacity, and assess performance using straightforward, data-driven approaches. You will learn to clean and preprocess open datasets, develop probabilistic demand models, establish daily allocation optimisation, and evaluate simple rebalancing policies to measure service levels and enhance real-world system reliability.
Elevify advantages
Develop skills
- Bike-share demand modelling: build Poisson and time-series models quickly.
- Capacity and queue analysis: calculate shortages, overflows, and service levels.
- Optimisation for fleets: set up LP and MIP models for daily bike allocation.
- Scenario and policy testing: evaluate rebalancing rules under peak-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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