Design a Lab-Automation Pipeline for a Bangalore Materials Startup
Overview
What this challenge is about.
Design a lab-automation pipeline for a materials startup, including an active-learning loop and rollout plan, to earn a verifiable certificate.
The scenario
The startup (around 18 people, recent USD 8 million Series A) is targeting battery-electrolyte additives and is betting the lab automation investment will compress its discovery cycle from 12 weeks to 3.
The Brief
What you'll do, and what you'll demonstrate.
Architect and plan the rollout of a closed-loop active-learning lab pipeline for a materials-discovery startup.
Earning criteria — what you'll demonstrate
- Design a multi-component AI/ML system across data, model, orchestration, and observability layers
- Specify an active-learning loop with realistic human-in-the-loop checkpoints
- Make and justify tooling decisions for an MLOps stack
- Plan a rollout that respects a real engineering team's capacity
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
AI for Science and Engineering
Master · Applied Ai
Strong alignment
This challenge maps to AI for Science and Engineering 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.
- Systems Architecture
Apply systems architecture to solve real industry problems and demonstrate production-level capability.
- Active Learning
Apply active learning to solve real industry problems and demonstrate production-level capability.
- Mlops Design
Apply mlops design to solve real industry problems and demonstrate production-level capability.
- Scientific Ml
Apply scientific ml to solve real industry problems and demonstrate production-level capability.
- Experiment Orchestration
Apply experiment orchestration to solve real industry problems and demonstrate production-level capability.
- Stakeholder Communication
Apply stakeholder communication 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
Translating a CTO ambition into a 90-day plan a cross-functional team can execute is core AI PM work.
This challenge sharpens
- stakeholder-communication
- active-learning
- mlops-design