Building Reliable Edge AI Starts with Mastering Embedded Data
Data Foundations for AI: Preparation, Quality, and Maintenance
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 3 to 5 day workshop 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 a 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 device 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 delivered online and tailored exclusively for one company at a time. Multiple developers from your team can join, all benefiting from a dedicated, hands-on session customized to your specific requirements and goals.
Workshop Agenda
Day 1: Introduction to Embedded Data Programming
- Introduction to data-driven design
- o ITTIA DB Lite AI & MCU devices
- MCU 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
- Deploy an ML model to embedded devices
- Code size, footprint, and data management efficiency
- Data safety, persistence and flash recovery mechanisms
- Protecting training data, inference results, and system logs (TLS, AES)
- End-to-end visibility with ITTIA Analitica and ITTIA Data Connect
- Hands-on exercises
Day 3: Building an Edge AI Pipeline
- Training an ML model with TensorFlow, PyTorch
- Convert the model and deploy to resource-constrained devices
- Application design and decision-making logic
- Performance statistics, instrumentation and optimization: throughput and latency
- Implementation of communication interfaces (TCP/IP, UART)
- Power and resource management
- Update, diagnostics, and lifecycle management
- Hands-on exercises
Days 4 and 5: Collaboration
- Collaborative session to define customer-specific use cases, requirements, and success criteria
- Rapid prototyping aligned with real-world application scenarios
- Architecture design tailored to target hardware, software stack, and constraints
- Integration of data pipelines, analytics, and AI components based on project needs
- Development of a working proof-of-concept demonstrating key functionalities
- Validation against performance, reliability, and operational requirements
- Creation of a case study highlighting outcomes, insights, and business value
- Knowledge transfer and recommendations for scaling to production
- Hands-on engagement to ensure practical, implementation-ready results
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. Demonstration candidates include:
Anomaly Detection in an Electric Motor
In this hands-on demonstration, participants act as embedded engineers using microcontroller devices to capture motor current data and train an on-device AI model with a tool such as NanoEdge AI Studio to detect anomalies in real time. With ITTIA DB Lite AI managing and storing data deterministically, raw signals are transformed into actionable insights, enabling a complete predictive maintenance solution directly at the edge.
Plant Leaf Disease Identification
In this hands-on demonstration, participants tackle early plant disease detection using microcontroller devices to capture leaf images and run real-time AI inference on-device with a tool such as STM32Cube.AI. Powered by ITTIA DB Lite AI, each prediction is stored with rich metadata, transforming individual detection events into actionable insights, enabling smarter, faster decisions for healthier and more productive crops, directly at the edge.
Data-Centric Edge AI for Weather Station Devices
This hands-on demonstration introduces developers to building data-centric Edge AI for weather monitoring and predictive maintenance, covering how meteorological data is captured, managed deterministically, and transformed into AI-ready features on-device. Through hands-on exercises, participants learn to integrate edge hardware and software to create reliable, real-time pipelines that detect anomalies and enable explainable intelligence directly at the edge.
Medical Device Predictive Maintenance
This hands-on demonstration introduces developers to building data-centric Edge AI for medical device monitoring and predictive maintenance, focusing on how physiological data, such as blood glucose and heart rate, is captured, managed deterministically, and transformed into AI-ready features on-device. Through hands-on exercises, participants learn to integrate hardware and software to enable real-time anomaly detection and reliable, explainable intelligence directly at the edge.
Course Details
Duration: 3 to 5 days
- Group discounts are available on the registration form.
Workstation: Attendees must have a Windows PC laptop and MCU device.
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
- Comprehensive lecture materials and step-by-step lab manuals
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
Workshop attendees will receive ITTIA DB Platform certification. This certification validates hands-on expertise in using the ITTIA DB Platform on MCU 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 MCU 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 participants.
In the unlikely event that ITTIA must cancel a workshop on short notice due to unforeseen circumstances, the sole and exclusive liability of ITTIA 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.
