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.

The RISC-V ecosystem has evolved from a specialized open-source Instruction Set Architecture (ISA) into a prominent architecture gaining substantial market traction in edge computing, IoT, automotive sectors, AI acceleration, and server-grade processors. Industry analysis highlights a significant skills gap: there are fewer than 5,000 RISC-V chip designers worldwide, contrasted with over 15,000 open roles in the semiconductor industry. Current recruitment trends indicate that employers seek candidates proficient in RISC-V architecture alongside SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain expertise. The most rapidly growing areas include automotive-grade RISC-V (ISO 26262 compliance), server-class processors featuring AIA interrupt controllers and multi-core coherence, and edge AI inference NPUs. Companies such as SiFive, Qualcomm, and Western Digital are accelerating RISC-V initiatives, intensifying the demand for engineers capable of unifying architecture specification, silicon implementation, firmware, and software stack development within a single skill set.