Model Bogotá's Bike-Share Network as a Graph for Overnight Rebalancing
Overview
What this challenge is about.
Build a directed graph from bike-share trip data, run centrality and route analyses, then earn your verifiable certificate.
The scenario
Bogotá's public bike-share scheme serves daily commuters across a dense, hilly city where ridership flows strongly downhill in the morning, leaving uphill stations starved and valley stations overflowing. Overnight truck rebalancing is the operator's main lever to reset the network before the morning peak, and route-planning quality directly drives how many riders find a bike or a free dock.
The Brief
What you'll do, and what you'll demonstrate.
Decide which overnight truck-route changes will most reduce morning bike and dock shortages, using graph metrics computed from the network's own trip history.
Earning criteria — what you'll demonstrate
- Translate an operational logistics question into an explicit directed weighted graph schema and defend the modeling choices
- Apply betweenness centrality, constrained shortest-path, and strongly-connected-component analysis correctly and interpret each in plain operational terms
- Combine trip-flow data with station coordinates to produce a geospatial network view that a non-technical reader can act on
- Convert graph metrics into specific, numbered, evidence-backed operational recommendations
- Communicate technical analysis to an operations audience without jargon
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Graphs
Apply graphs to solve real industry problems and demonstrate production-level capability.
- Networkx
Apply networkx to solve real industry problems and demonstrate production-level capability.
- Shortest Path
Apply shortest path to solve real industry problems and demonstrate production-level capability.
- Centrality Analysis
Apply centrality analysis to solve real industry problems and demonstrate production-level capability.
- Data Storytelling
Apply data storytelling to solve real industry problems and demonstrate production-level capability.
- Geospatial Analysis
Apply geospatial analysis to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Graph / Network Data Engineer
Modeling a real logistics network as a directed weighted graph and computing centrality and component metrics on it is the core daily work of engineers who build routing, recommendation, and fraud-detection systems on graph data.
This challenge sharpens
- graphs
- networkx
- centrality-analysis
Operations Research / Logistics Engineer
Turning constrained shortest-path results into drivable overnight routes mirrors how logistics engineers optimize fleet and dispatch decisions under real time and capacity limits.
This challenge sharpens
- shortest-path
- networkx
- graphs
Analytics Engineer
Packaging network analysis into a map and a memo a non-technical team can act on is exactly how analytics engineers convert raw event data into operational decisions.
This challenge sharpens
- geospatial-analysis
- data-storytelling
- centrality-analysis