Build an Interactive Carbon-Emissions Explorer for a Climate Nonprofit
Overview
What this challenge is about.
Build an Interactive Carbon-Emissions Explorer for a Climate Nonprofit. Intermediate challenge in code. Writing production code that solves real engineering ...
The Brief
What you'll do, and what you'll demonstrate.
Ship a journalist-grade interactive emissions explorer with embed support and explicit data-caveat treatment.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Design coordinated multi-view interactive visualizations
- Communicate methodology caveats honestly without overwhelming readers
- Run lightweight usability tests with non-technical experts
- Ship for embedding in third-party contexts
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Data Visualization
Master · Data Engineering
Strong alignment
This challenge maps to Data Visualization 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.
- Interactive Visualization
Apply interactive visualization to solve real industry problems and demonstrate production-level capability.
- D3
Apply d3 to solve real industry problems and demonstrate production-level capability.
- Observable
Apply observable 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.
- User Testing
Apply user testing to solve real industry problems and demonstrate production-level capability.
- Data Journalism
Apply data journalism 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:
AI Product Designer
Designing interactive data products that hold up to expert scrutiny is a core AI product designer skill, especially at climate, public-policy, or media organizations.
This challenge sharpens
- interactive-visualization
- data-storytelling
- user-testing
Data Scientist
Communicating multi-year methodology shifts honestly is the kind of data-storytelling responsibility data scientists carry on public-facing work.
This challenge sharpens
- data-storytelling
- data-journalism
- interactive-visualization
AI Product Manager
Scoping for embed-readiness and external usability tests mirrors AI PM work on data products with external audiences.
This challenge sharpens
- user-testing
- data-storytelling
- interactive-visualization