
Most engineers know the buzzwords — MQTT, OPC UA, Sparkplug B,
Unified Namespace. Very few have actually built one from scratch.
This course closes that gap.
In this hands-on masterclass, you will build a complete industrial
data pipeline on your own laptop using entirely free tools. No
vendor lock-in. No cloud subscription required. No hardware needed.
Just your machine, a working internet connection, and the same
open-source stack that real plants are deploying right now.
WHAT YOU WILL BUILD:
A complete end-to-end Unified Namespace — from OPC UA source through
Sparkplug B encoding, MQTT brokering, Python subscribers, time-series
storage, and live Grafana dashboards. Every layer. Every connection.
Every failure mode tested.
THE STACK YOU WILL MASTER:
- Ignition Edge — as OPC UA client and Sparkplug B publisher
- HiveMQ Community Edition — as your MQTT broker
- Eclipse Tahu — the Sparkplug B reference library
- Python with paho-mqtt — custom publishers and subscribers
- Node-RED — low-code MQTT subscriber in five minutes
- InfluxDB v2 — time-series historian for plant data
- Grafana — live plant dashboards from real data
- Azure IoT Hub — cloud bridge for multi-site analytics
WHO THIS COURSE IS FOR:
OT engineers being asked to build digital infrastructure they have
never seen before. Controls and automation engineers stepping into
IIoT. IT engineers entering the manufacturing space. Anyone who has
attended a UNS webinar and wants to actually build one, not just
understand it conceptually.
WHY THIS COURSE IS DIFFERENT:
Every other course stops at theory or covers one piece of the stack.
This course builds the complete vertical slice — OPC UA server to
Grafana dashboard — in a single coherent narrative. You will see
every component connect to the next. You will see failures and
understand why they happen. You will leave with a working demo you
can show in a job interview or a client meeting.
The instructor brings 20 years of plant-floor OT engineering
experience — hands-on PLC, DCS, SCADA, and instrumentation — combined
with enterprise IIoT advisory work across metals, chemicals, pharma,
and semiconductor verticals. This is not academic content. Every
pattern in this course came from a real plant problem.
PREREQUISITES:
Basic understanding of industrial automation concepts. Familiarity
with Python is helpful but not required — all scripts are provided
and explained line by line.
By the end of this course you will have built something real. Not a
toy project. A complete industrial data backbone — the same
architecture that powers Industry 4.0 at scale.