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Extract Structured Lease Terms for a Commercial Real-Estate Platform

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

Extract lease terms from 500 PDFs with regex and a small model, then evaluate accuracy. You get a verifiable certificate.

The scenario

The proptech (~70 staff) processes ~2,800 leases per month for brokers across Germany, Netherlands, and the UK; manual extraction currently costs ~EUR 22 per lease.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Automate per-field lease extraction at 95% accuracy with a human-review fallback for low-confidence rows.

Earning criteria — what you'll demonstrate

  • Build a hybrid rule + ML extraction pipeline on real PDF data
  • Calibrate per-field confidence to route to human review
  • Evaluate IE accuracy per field, not just overall
  • Translate extraction performance into deployment recommendations

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Aligned coursework coming soon.

Careers

Career paths this challenge builds toward

Completing this challenge demonstrates skills that transfer directly to these roles:

NLP Engineer

Owning an IE pipeline on real PDFs with calibrated confidence is the day-one work of NLP engineers at any vertical-document AI startup.

This challenge sharpens

  • information-extraction
  • named-entity-recognition
  • pdf-parsing

AI Engineer

Wiring the human-in-the-loop fallback plus the rollout plan is core AI-engineer work at vertical-AI vendors.

This challenge sharpens

  • human-in-the-loop
  • confidence-calibration
  • pdf-parsing

Data Engineer

Designing the extraction pipeline and gold-set evaluation is the data-engineering backbone of any IE product.

This challenge sharpens

  • information-extraction
  • evaluation
  • pdf-parsing

One more thing

You can put a credential on your CV by Friday.