Format
Real-time online intensive course with lifetime access to lesson recordings and content.
The “Using Shelly Devices With Amazon AWS - September 2025” is a hands-on, advanced-level course developed by Shelly Academy in collaboration with SoftUni Global. This training focuses on integrating Shelly devices with AWS to enable scalable, cloud-based automation, monitoring, and analytics.
Over the course of four live sessions, you will explore how to connect Shelly devices securely to AWS using MQTT, learn how to create event-driven automations using AWS Lambda and IoT Rules Engine. You'll also learn how to manage and store their data using Timestream, organize devices into structured environments with SiteWise and build dashboards with Managed Grafana.
Whether you're deploying Shelly in a smart building, industrial setting, or smart home, this course will give you the tools to manage data flows, detect anomalies, and visualize everything in real time.
Get ready to bring your Shelly automations to the cloud — and beyond.
Real-time online intensive course with lifetime access to lesson recordings and content.
22 – 25 September
Monday to Thursday. Each lesson starts at 6:00 PM Central European Summer Time (CEST) and lasts 2.5 to 3 hours.
Renowned certification is provided after a successful course completion.
We've partnered with SoftUni, a global leading software academy, to ensure that you receive top-notch education and guidance from industry professionals. With the completion of this course, you will receive an official certificate from SoftUni and Shelly Academy.
Overview of AWS IoT Core and its role in IoT ecosystems
Connecting Shelly devices to AWS IoT using MQTT
Using device certificates for secure communication
Executing Remote Procedure Calls (RPC) over MQTT
Doing hands-on exercises to practice new knowledge
Logging and analyzing time-based metrics with Amazon Timestream
Organizing structured device data with Amazon SiteWise
Building real-time dashboards with Amazon Managed Grafana
Doing hands-on exercises to practice new knowledge
Using Amazon SiteWise to model assets and compute maintenance metrics
Exploring historical patterns and anomalies using Amazon Q
Solution for detecting abnormal device behavior using historical data
Doing hands-on exercises to practice new knowledge