Edge Analytics: Rules Engines on Device
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Advanced IoT Development · Advanced

Edge Analytics: Rules Engines on Device

Run lightweight scoring at the edge with bounded CPU budgets.

7 weeks · Live online cohort · Cohort start 2026-05-05 · ₩1,380,000

Cover visual for Edge Analytics: Rules Engines on Device

Overview

Move filtering closer to sensors using deterministic rule packs, shadow deployments, and offline caches. You compare batch vs streaming mini-pipelines with measurable watt budgets.

Included focus areas

  • CPU budget worksheets per pipeline stage
  • Shadow deployment pattern with kill switch
  • Offline cache sizing exercises
  • Deterministic seeding for reproducible demos
  • Heatmaps for sensor fusion conflicts
  • Observability hooks without shipping PII
  • Edge container lifecycle drills

Outcomes you can evidence

  • Publish rule packs with signed manifests
  • Demonstrate graceful degradation when uplink drops
  • Present watt comparisons across two firmware builds

FAQ

GPU acceleration?

Not covered—labs stay MCU-class with documented CPU ceilings.

Cloud credits?

No cloud credits are bundled; sandbox budgets are classroom-sized only.

Certification?

Completion letters available; third-party exam vouchers are not included.

Participant notes

“Shadow deploy lab mirrored how we stage firmware today—minus the GPU rabbit holes.”
— Devon · Regional cold-chain startup
“Kill switch drill felt rushed on Tuesday, but office hours clarified the rollback path.”
— Sora K. · 4/5 · survey