Build a Public Open-Data Dashboard for Urban Mobility
Overview
What this challenge is about.
You analyze 10 years of cyclist-collision data around new bike lanes and publish an interactive dashboard. Earn a verifiable certificate.
The scenario
The nonprofit (8 staff + volunteer board) produces civic-data work that often gets cited by local press; a single methodological error can hand opponents a year-long talking point.
The Brief
What you'll do, and what you'll demonstrate.
Publish a defensible, interactive dashboard on cyclist-injury-rate change after a protected-lane rollout, with a methods note that survives political scrutiny.
Earning criteria — what you'll demonstrate
- Work end-to-end with messy open civic data
- Apply before/after analysis with appropriate confounders
- Communicate uncertainty visually for a public audience
- Defend analytical choices in writing to a non-technical board
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Applied Data Analysis and Practical Data Science
Master · Data Engineering
Strong alignment
This challenge maps to Applied Data Analysis and Practical Data Science at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Exploratory Data Analysis
Apply exploratory data analysis to solve real industry problems and demonstrate production-level capability.
- Data Wrangling
Apply data wrangling 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.
- Data Visualization
Transform complex data into clear, insightful visual representations.
- Data Storytelling
Apply data storytelling to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Data Scientist
Public civic-data work with a defensible methods note is a portfolio piece any junior data scientist can point to in interviews to prove communication chops.
This challenge sharpens
- exploratory-data-analysis
- data-storytelling
- geospatial-analysis
Data Engineer
Wrangling messy open data into a snapshotted, versioned pipeline is exactly how data engineers operationalize public-data work.
This challenge sharpens
- data-wrangling
- python
- geospatial-analysis
AI Product Designer
Designing an honest interactive dashboard for a public audience is a transferable craft for designing data-driven product surfaces.
This challenge sharpens
- data-visualization
- data-storytelling
- exploratory-data-analysis