Storytelling Visualization of an Autonomous Vehicle Test Campaign
Overview
What this challenge is about.
Analyze 12,000 autonomous vehicle test runs to design an executive deck and engineering script. Earn a verifiable certificate.
The scenario
The startup (around 220 staff, around USD 90 million raised, no public road testing yet) is preparing a Series B and the test campaign is the central data point for the next investor narrative.
The Brief
What you'll do, and what you'll demonstrate.
Tell the same test campaign story for both the board and the engineering team without distorting the underlying numbers for either audience.
Earning criteria — what you'll demonstrate
- Adapt the same data story to two different audiences without distortion
- Apply chart-design conventions consistently across an artifact set
- Identify the headline metric per audience and lead with it
- Reason about ethical limits of chart-design persuasion
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.
- Data Storytelling
Apply data storytelling to solve real industry problems and demonstrate production-level capability.
- Audience Adaptation
Apply audience adaptation to solve real industry problems and demonstrate production-level capability.
- Chart Design
Apply chart design to solve real industry problems and demonstrate production-level capability.
- Exploratory Data Analysis
Apply exploratory data analysis to solve real industry problems and demonstrate production-level capability.
- Business Storytelling
Apply business storytelling to solve real industry problems and demonstrate production-level capability.
- Honesty In Charts
Apply honesty in charts 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 Manager
Turning model and test data into board and engineering narratives is a primary day-to-day skill of an AI PM.
This challenge sharpens
- data-storytelling
- audience-adaptation
- business-storytelling
Data Scientist
Communicating results honestly across audiences is repeatedly cited as the differentiator between mid-level and senior data scientists.
This challenge sharpens
- data-storytelling
- chart-design
- exploratory-data-analysis
AI Product Designer
Designing chart conventions that hold up across artifacts is the kind of systems-design thinking AI product designers bring to internal tooling.
This challenge sharpens
- chart-design
- honesty-in-charts
- audience-adaptation