Microcontroller Training in Nantes

This instructor-led, live training in Nantes (online or onsite) is designed for intermediate-level embedded systems engineers and AI developers who want 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 fundamentals of TinyML and its advantages for edge AI applications.
• Configure a development environment tailored for TinyML projects.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Utilize TensorFlow Lite and Edge Impulse to build real-world TinyML solutions.
• Optimize AI models to meet power efficiency and memory limitations.

This instructor-led, live training in Nantes (online or onsite) is designed for engineers who want to master embedded C programming for various microcontroller types across different processor architectures (8051, ARM CORTEX M-3, and ARM9).

In this instructor-led live training in Nantes, 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 niche open-source instruction set architecture (ISA) into a mainstream architectural choice, gaining significant market traction across edge computing, the Internet of Things (IoT), automotive systems, AI acceleration, and server-grade processors. Industry analyses highlight a pressing talent gap: there are fewer than 5,000 RISC-V chip designers worldwide, compared to an estimated 15,000+ open roles within the semiconductor sector. Current hiring trends indicate that employers are prioritizing candidates who possess RISC-V architecture proficiency alongside skills in System-on-Chip (SoC) design, RTL verification using UVM and SystemVerilog, AI accelerator development, Rust-based systems programming, confidential computing, and open-source toolchain expertise. The most rapidly growing competency areas include automotive-grade RISC-V (ISO 26262), 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 their RISC-V development efforts, thereby increasing demand for engineers capable of bridging architecture specifications, silicon implementation, firmware, and software stack development within a unified skill set.