A Practical Online Workshop with Complete Guide

Are you ready for AI Edge Data Computing? Are you interested in managing, analyzing and storing data on microcontroller (MCU) devices? Are you interested in learning how to prepare data for AI models running on microcontrollers? If you say yes to any of these questions, then this is the right workshop for you. We will rapidly teach and provide guidelines in our hands-on workshop for which you will be required to purchase an assigned STM32 device. This is a hands-on workshop; be prepared to follow the instructor step by step.

We will initially introduce you to data management concepts on MCU devices where real-time time-series data must be first captured, organized, and validated with minimal latency, then processed and analyzed to extract meaningful insights. Efficient storage preserves historical data within tight memory limits, enabling trend detection, anomaly detection, and predictive decisions locally, turning MCU devices into intelligent edge nodes that do not rely on constant cloud access.

Data management and data preparation for microcontrollers—including AI enablement and more—present unique challenges due to the resource constraints of these devices. MCU devices typically have limited RAM, storage, and processing power, making it difficult to handle high-frequency sensor data, perform real-time preprocessing, and store structured or time-series data efficiently.

Preparing data for AI involves cleaning, normalizing, and sometimes extracting features, all of which must be done with minimal latency and deterministic execution. Additionally, ensuring data integrity, supporting intermittent connectivity, and minimizing power consumption further complicate the process. These challenges require lightweight, optimized data management solutions and special knowledge and skills that can operate reliably within the tight memory and timing constraints of MCU environments.

This workshop is designed to address these challenges through a hands-on approach, guiding participants to install ITTIA DB Lite, run examples, explore features, evaluate ML integrations, and measure performance and AI capabilities on MCU devices.

The Training Advantage

Our specialized training delves into the critical data architecture of modern embedded systems. You will learn:

• ITTIA DB Lite, STM32 and ML data management requirements.
• Data collection, data preparation, and data management techniques.
• Data quality control, data security and data integration practices.
• The benefits of saving and embedding ITTIA DB Lite on STM32 devices.

Go Hands-On

Gain practical experience and collaborate with our experts to:

• Together we will build a data driven campaign for an embedded system with ITTIA DB Lite and STM32 devices.
• We will introduce techniques for integrating ITTIA DB Lite with AI/ML tools, RTOS, and STM32 devices.
• We will address various data challenges on STM32 devices, ensuring immediate benefits for your next projects.

Why This Training Matters

Regardless of your experience, our focused approach will rapidly bring you up to speed on cutting-edge data management options for STM32 devices. You can unlock the full value of data pouring in from sensors, actuators, and gateway devices for machine learning and artificial intelligence with data management and analytics. You will save serious learning time, benefit from our decades of experience and R&D and prepare yourself on time for the next wave of innovation.