Enterprise AIoT Systems Architecting

Build complete edge-to-cloud connected systems: from device sensors to cloud message brokers, backend processors, databases, and dashboards.

6 Weeks / 48 Hours Hands-on Labs

Certificate of AIoT Architect Awarded

Training Covering Area

An advanced training program detailing how to design scalable, secure, and resilient Internet of Things systems incorporating AI pipelines at the gateway and cloud.

Module 1: Connected Devices & Protocols

Edge topologies: Direct cellular connection, gateway nodes, and mesh networking
JSON payload serialization vs compact binary structures (Protobuf, MessagePack)
MQTT specification: QoS levels, keep-alive timers, wildcard topics, and persistent sessions
CoAP (Constrained Application Protocol) and security comparison with HTTPS

Module 2: Cloud Ingestion & Broker Infrastructure

Setting up AWS IoT Core / Azure IoT Hub registries and X.509 client certificate management
Device Shadows / Twins: Syncing state between offline devices and cloud interfaces
Configuring IoT rule engines to route data streams to databases, lambda functions, or brokers
Deploying self-hosted MQTT brokers (Mosquitto/EMQX) using Docker and Linux servers

Module 3: Ingestion pipelines & Timeseries Databases

Writing backend consumer services in Node.js and Python for high-frequency telemetry
Designing database schemas for timeseries optimization (InfluxDB, TimescaleDB, PostgreSQL)
Caching telemetry data with Redis to ensure low latency for web applications
Configuring stream processing tools (Apache Kafka, RabbitMQ) for processing pipelines

Module 4: React Dashboards & Device Control

Building responsive React web dashboards to visualize telemetry data streams in charts
Integrating WebSockets to push live updates directly to users without polling APIs
Executing bidirectional commands: Remote reboot, GPIO configuration, and variable tuning
Alerting pipelines: Integrating rule thresholds with email, Slack, and SMS notification APIs