Design a Model-Monitoring Dashboard for an MLOps Platform
Overview
What this challenge is about.
Design a single-page monitoring dashboard for three ML models, analyzing health, changes, and drift. Build your prototype and earn a verifiable certificate.
The scenario
The MLOps company (around 90 staff, around EUR 22 million ARR) has identified dashboard usability as the second-most-cited reason for churn in last quarter's customer interviews.
The Brief
What you'll do, and what you'll demonstrate.
Redesign the primary model-monitoring dashboard so the four core questions are answered in the order users actually ask them.
Earning criteria — what you'll demonstrate
- Apply visual-hierarchy principles to a dense operational dashboard
- Match chart type to data type for ML-specific metrics
- Design for the user's actual question order, not the data team's mental model
- Communicate redesign rationale defensibly to a product team
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.
- Dashboard Design
Apply dashboard design to solve real industry problems and demonstrate production-level capability.
- Visual Hierarchy
Apply visual hierarchy to solve real industry problems and demonstrate production-level capability.
- Chart Selection
Apply chart selection to solve real industry problems and demonstrate production-level capability.
- Ml Metrics
Apply ml metrics to solve real industry problems and demonstrate production-level capability.
- Streamlit
Apply streamlit to solve real industry problems and demonstrate production-level capability.
- Redline Design
Apply redline design 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
Redesigning a dense ML-product dashboard with explicit rationale is the exact day-one work of an AI product designer at any MLOps or analytics platform.
This challenge sharpens
- dashboard-design
- visual-hierarchy
- chart-selection
AI Product Manager
Owning the four-question framing and the customer-test script is exactly how AI PMs scope product redesigns.
This challenge sharpens
- dashboard-design
- ml-metrics
- redline-design
MLOps Engineer
Understanding what makes a good monitoring surface translates into stronger MLOps platform engineering decisions.
This challenge sharpens
- ml-metrics
- streamlit
- dashboard-design