Implement predictive machine maintenance alerts, supply chain trackers, and industrial control network guards.
Industry 4.0 fuses physical assembly plants with cyber-physical processing. Operational technology (OT) systems rely on IoT sensors and machine learning checkpoints to predict factory faults, organize component pipelines, and shield heavy machinery from rogue digital commands.
Autonomous procurement agents that monitor warehouse counts, select qualified parts vendors, and draft purchase orders.
Vibration telemetry anomaly classifiers predicting bearing failures on turbine shafts using autoencoders.
Scada operational dashboards displaying assembly yields, machine uptime metrics, and defect ratios.
Supplier risk cohort analysis dashboards, factory footprint optimization models, and energy consumption metrics.
Industrial control system firewalls, Modbus protocol encryption layers, and OT network activity logs.
IoT core gateway connection pipelines deployed in the cloud to aggregate and store sensor telemetry from industrial factory equipment in real time.
Practice with 12 structured tasks categorized by difficulty.
Develop a basic dashboard warning operators when assembly line thermometer telemetry crosses safe thresholds.
Write a SQL database schema capturing state shifts, diagnostic codes, and operators across shift hours.
Write a network scanner verifying that factory machinery control points do not use default manufacturer credentials.
Build a rule-based script alerting managers on Slack when critical part bins fall below base counts.
Write a simple script forwarding simulated factory temperature data to an AWS S3 raw directory.
Core Skills
Core Skills
Core Skills
