Microcontroller Training in Turin

This instructor-led, live training in Turin (online or onsite) is designed for intermediate-level embedded systems engineers and AI developers who aim to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

Upon completion of this training, participants will be able to:

• Grasp the core principles of TinyML and its advantages for edge AI applications.
• Configure a development environment suitable for TinyML projects.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Leverage TensorFlow Lite and Edge Impulse to build practical TinyML solutions.
• Enhance AI models for better power efficiency and to meet memory limitations.

This instructor-led, live training in Turin (online or onsite) is designed for engineers who want to learn how to use embedded C to program various microcontrollers based on different processor architectures (8051, ARM CORTEX M-3, and ARM9).

In this instructor-led, live training in Turin, participants will learn how to program the Arduino for real-world usage, such as to control lights, motors and motion detection sensors. This course assumes the use of real hardware components in a live lab environment (not software-simulated hardware).

By the end of this training, participants will be able to:

• Program Arduino to control lights, motors, and other devices.
• Understand Arduino's architecture, including inputs and connectors for add-on devices.
• Add third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to extend Arduino's functionality.
• Understand the various options in programming languages, from C to drag-and-drop languages.
• Test, debug, and deploy the Arduino to solve real world problems.

This instructor-led, live training in Turin (online or onsite) is designed for engineers seeking to master the design principles of microcontrollers.

The Raspberry Pi is a compact, single-board computer.

Through this instructor-led live training, participants will learn how to configure and program the Raspberry Pi to function as an interactive and robust embedded system.

Upon completion of this training, participants will be able to:

• Configure an IDE (Integrated Development Environment) to optimize development productivity.
• Program the Raspberry Pi to manage devices such as motion sensors, alarms, web servers, and printers.
• Grasp the Raspberry Pi's architecture, including input/output ports and connectors for add-on devices.
• Evaluate the available options regarding programming languages and operating systems.
• Test, debug, and deploy the Raspberry Pi to address real-world challenges.

Audience

• Developers
• Hardware and software technicians
• Technical professionals across all industries
• Hobbyists

Format of the course

• A blend of lectures, discussions, exercises, and intensive hands-on practice.

Note

• The Raspberry Pi supports various operating systems and programming languages. This course utilizes Linux-based Raspbian as the operating system and Python as the programming language. To request a different setup, please contact us to arrange.
• Participants are responsible for purchasing their own Raspberry Pi hardware and components.

This instructor-led, live training in Turin (online or onsite) is designed for engineers aiming to write, load, and run machine learning models on compact embedded devices.

By the end of this training, participants will be able to:

• Install TensorFlow Lite.
• Load machine learning models onto an embedded device to enable speech detection, image classification, and similar functions.
• Integrate AI into hardware devices without relying on network connectivity.