Building Reliable Edge AI Starts with Mastering Embedded Data

Hands-On Training Workshop: Build, Learn, Deploy

Overview

Learn how to design digital and build data driven embedded systems from the ground up quickly and easily with this in-depth laboratory-based design workshop and receive software training to simplify the design process and accelerate continuous professional development. This workshop is a 3 day collaboration between ITTIA and STMicroelectronics is aimed at edge designers and embedded systems engineers who need to design high performance embedded systems with microcontrollers and microprocessor devices.

During the workshop, you will learn how to select an STM32 device and software components to build deterministic data-driven AI applications for the embedded edge. You will then design, code, implement and test two safety-concious real-time data applications with STM32H7, STM32N6, and STM32MP2 hardware. Engineering concepts, theoretical materials, and step-by-step design procedures are taught first, then put into practice with numerous laboratory exercises.

You will learn how to build an AI-edge embedded system that is tightly integrated with the right hardware platform, real-time firmware, robust on-device data management, and optimized AI models to deliver deterministic, safe, and power-efficient intelligence at the edge. In this hands-on workshop, engineers learn how AI transforms embedded systems from fixed-function controllers into adaptive, data-driven platforms, mastering the full development lifecycle: from device selection and firmware design to trustworthy, real-time inference in production deployments.

Workshop Dates and Locations

These workshops are hosted at STMicroelectronics offices throughout the United States of America.

Workshop Agenda

Day 1: Introduction to Embedded Data Programming

• Introduction to data-driven design
• STM32 development boards and kits
  • Real-time operating systems (RTOS) and bare metal options
  • Hardware Abstraction Layer (HAL) & low-level drivers
• The edge data processing pipeline
  • Edge data streaming, time series, tagging, and meta data
• Data modeling for edge devices
  • Event logging and access control
  • Anomaly detection in an electric motor
  • Plant leaf disease identification
• Low-level access to peripherals (GPIO, ADC, UART, SPI, I2C, timers, DMA)
• Implementing simple device data capture with ITTIA Data Connect and ITTIA Analitica
• Hands-on exercises

Day 2: Data-Driven Firmware Design

• Data cleaning with deterministic buffers, time windows, aggregation, and fusion algorithms
• Auto ML with NanoEdge AI Studio
• Deploy ML library to STM32H5
• Code size, footprint, and data management efficiency
• Data safety and flash recovery
• Protecting training data, inference results, and system logs (TLS, AES)
• Visualize data with ITTIA Analitica and ITTIA Data Connect
• Hands-on exercises

Day 3: Building an Edge AI Pipeline

• STM32Cube.AI and the ST Microelectronics Model Zoo
• Training an ML model with TensorFlow, PyTorch
• Convert the model and deploy to STM32N6
• Application and decision logic
• Performance statistics, instrumentation and optimization: throughput and latency
• Communication stacks (TCP/IP, UART)
• Power and resource management
• Update, diagnostics, and lifecycle management
• Hands-on exercises

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Workshop Sample Applications

During this hands-on workshop, you will be trained to design, build, and deploy two real-world, data-driven AI applications, gaining practical skills you can immediately apply to embedded and edge systems.

Anomaly Detection in an Electric Motor

During the workshop, participants step into the role of an embedded engineer responsible for keeping an electric motor running reliably in a demanding real-world environment. Using STM32 devices as the hardware foundation, they begin by capturing live motor current signals—no extra sensors, no cloud dependency, just raw electrical behavior at the edge. With NanoEdge AI Studio, the team trains an on-device AI model that learns what "normal" looks like for the motor and continuously adapts as operating conditions change.

As the motor runs, subtle abnormalities begin to appear, slight variations in current, brief bursts of noise, early warning signs invisible to traditional threshold-based logic. The AI detects these anomalies in real time, while ITTIA DB Lite persistently stores and organizes the results on the device itself. Together, AI and data management transform raw signals into insight: anomaly frequency, duration, and severity are analyzed to compute a live motor health score, alongside on-device statistics such as average current, peak noise levels, and anomaly counts. By the end of the session, participants have built a complete predictive maintenance solution, one that demonstrates how AI plus deterministic embedded data management enables smarter, safer, and more reliable industrial systems directly at the edge.

Plant Leaf Disease Identification

During the workshop, participants step into the field as embedded innovators tackling one of agriculture’s most pressing challenges: detecting plant disease early enough to protect crop yield. Using STM32 devices as the edge platform, they build a compact vision-based system that captures images of plant leaves directly in the field. With STM32Cube.AI and models from the ST Edge AI Model Zoo, participants deploy an optimized AI model that performs real-time disease identification on-device, delivering fast, accurate results without relying on cloud connectivity.

As images are analyzed, ITTIA DB Lite becomes the intelligence backbone of the system. Each inference is stored alongside rich metadata, including image ID, predicted disease label, confidence score, timestamp, and GPS location. Over time, this “AI + Data” pipeline transforms individual detection events into actionable insight: time-series image data reveals disease patterns, highlights emerging outbreak areas, and correlates plant health with soil and weather conditions. By the end of the session, participants have built a complete edge AI solution that demonstrates how deterministic data management and on-device intelligence work together to enable faster intervention, smarter decision-making, and healthier, more productive crops.

Course Details

Cost: USD $1,500 per participant (3-day program)

• Group discounts are available on the registration form.

Schedule: Monday–Wednesday, 9:00 AM – 5:00 PM

Lab Workstation: Attendees must bring a Windows PC laptop. STM32 devices will be provided.

All participants will work in pairs at a dedicated workstation. Registration is priced per individual seat; however, hands-on lab work is performed collaboratively. If you register as an individual, you may be paired with another attendee.

The workshop fee includes:

• Three (3) full days of expert-led, hands-on training
• Complimentary 12-month license of the ITTIA DB Platform software
• STM32 device hardware will be provided
• Comprehensive lecture materials and step-by-step lab manuals
• Daily lunch and refreshments

This immersive format ensures every participant leaves with practical experience, real working systems, and the confidence to apply AI-driven, data-centric embedded design techniques in real-world projects.

Edge Data AI Certification for STM32 Devices

Workshop attendees will receive ITTIA DB Platform certification. This certification validates hands-on expertise in using the ITTIA DB Platform on STM32 devices for deterministic data management, on-device data processing, and Edge AI–ready data handling. It demonstrates and validates the ability to design reliable, power-fail-safe, and AI-enabled embedded systems using proven data architectures, reducing development risk, accelerating time to production, and enabling high-quality, scalable solutions on STM32 platforms.

 

 

Past Workshop Participants

ITTIA and STMicroelectronics have delivered highly sought-after, hands-on workshops that attract engineers and innovation leaders from across multiple sectors. Our sessions are trusted by companies building real-world, data- and AI-driven embedded systems, and have been attended by teams from leading organizations committed to advancing intelligent edge technologies, including:

Abbott – Acuity Brands – Advances Energy – Applied materials – Avery Biomedical Devices, Inc. – Badger Meter – Cardios – Cat Wranglers
Cognosos Inc. – Continental AG – CPI – Declarative Futures – EDS – Emtech – Everspin – EXFO – Honeywell – Kellogg Northwestern
L3Harris – Magna International – Mayo clinic – Megavolt Labs – Milwaukee Tool – Mold Masters – Nidec Global Appliances – OTTO Engineering
Philips – Resideo – Schneider Electric – Siemens – Southland Sensing Ltd.  – TITOMA – TTI Floor Care – Wind River – Zetron/Codan

Audience

These immersive, hands-on workshops are built for embedded architects and engineers who are shaping the next generation of data-driven, AI-enabled edge systems and want more than theory, they want results. Through practical, expert-led sessions, participants learn how to select the right device platform, design deterministic real-time firmware, and implement robust on-device data management that elevates data to a first-class system asset. The program goes further by showing how to prepare and integrate optimized AI pipelines directly into embedded workflows, while addressing cybersecurity, functional safety, diagnostics, and long-term lifecycle management from day one. By the end of the workshop, engineers leave with the confidence, skills, and real-world experience needed to build intelligent, trustworthy, and future-proof embedded systems ready for production.

These workshops are highly technical, intended for professional engineers and are not suitable for the general public without relevant qualifications.

Cancellation & Registration Policy

To ensure a high-quality, hands-on learning experience, each ITTIA workshop is offered with a limited number of seats.

• Workshop Capacity: Minimum of 5 and maximum of 20 participants.
• Minimum Enrollment: If the minimum number of registrations is not met 10 days prior to the scheduled workshop date, the session may be cancelled, and all registered participants will receive a full refund.

In the unlikely event that ITTIA must cancel a workshop on short notice due to unforeseen circumstances, the sole and exclusive liability of ITTIA and STMicroelectronics shall be limited to the refund of the applicable course fees.

• Participant Cancellations: Registrations are non-refundable in cases where a participant is unable to attend. However, to maximize flexibility and value:
  • Your registration may be transferred to a colleague, or
  • Applied to a future ITTIA workshop of equal value.

To ensure fairness to all attendees and instructors, participants who are confirmed but do not attend the scheduled session remain responsible for the full workshop fee.

This policy allows us to deliver an immersive, instructor-led experience while maintaining the highest standards of quality, preparation, and technical depth.

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