Overview
What this challenge is about.
Map PETs across data-lifecycle stages, build a decision-tree poster, and write an 8-page board memo to earn your verifiable certificate.
The scenario
The Brussels consultancy (around 45 staff, EU regulatory + AI advisory) is positioning PETs strategy as its differentiated offer in the EU AI Act compliance market.
The Brief
What you'll do, and what you'll demonstrate.
Design a layered PETs strategy for an insurance AI use case that maps cost, risk, and EU AI Act alignment, and build a reusable decision framework.
Earning criteria — what you'll demonstrate
- Map PETs (DP, FL, SMPC, TEEs, synthetic data) to ML lifecycle stages
- Reason about accuracy + cost + privacy trade-offs at strategy level
- Align technical choices to EU AI Act articles
- Build a reusable decision framework for future engagements
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.
- Pets Strategy
Apply pets strategy to solve real industry problems and demonstrate production-level capability.
- Differential Privacy
Apply differential privacy to solve real industry problems and demonstrate production-level capability.
- Federated Learning
Apply federated learning to solve real industry problems and demonstrate production-level capability.
- Secure Computation
Apply secure computation to solve real industry problems and demonstrate production-level capability.
- Regulatory Alignment
Apply regulatory alignment to solve real industry problems and demonstrate production-level capability.
- Decision Frameworks
Apply decision frameworks 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 Solutions Architect
Designing PETs strategy at the board level and building reusable decision frameworks is exactly the work AI solutions architects do at AI consultancies and at regulated enterprises.
This challenge sharpens
- pets-strategy
- regulatory-alignment
- decision-frameworks
AI Safety Researcher
Translating privacy-research methods into deployable strategy is the AI safety work that bridges research and enterprise rollout.
This challenge sharpens
- differential-privacy
- federated-learning
- secure-computation
AI Product Manager
Reasoning about privacy/accuracy/cost trade-offs and aligning them to regulatory requirements is core AI PM work at any regulated AI product team.
This challenge sharpens
- regulatory-alignment
- decision-frameworks
- pets-strategy