Microcontroller Training in Dobrogea Sud-Est

This instructor-led, live training in Dobrogea Sud-Est (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. <\/p>

Upon completing this training, participants will be able to: <\/p>

• Comprehend the core principles of TinyML and its advantages for edge AI applications. <\/li>
• Configure a development environment tailored for TinyML projects. <\/li>
• Train, optimize, and deploy AI models on low-power microcontrollers. <\/li>
• Leverage TensorFlow Lite and Edge Impulse to create real-world TinyML solutions. <\/li>
• Optimize AI models to meet power efficiency requirements and memory limitations. <\/li> <\/ul>

This instructor-led, live training in Dobrogea Sud-Est (online or onsite) is designed for engineers seeking to master the use of embedded C for programming diverse microcontrollers across various processor architectures, including 8051, ARM CORTEX M-3, and ARM9.

In this instructor-led live training in Dobrogea Sud-Est, participants will learn how to program Arduino for practical applications, such as controlling lights, motors, and motion detection sensors. This course requires the use of real hardware components in a live lab environment, rather than software-simulated hardware.

Upon completing 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 adding peripherals.
• Integrate third-party components like LCDs, accelerometers, gyroscopes, and GPS trackers to expand Arduino's capabilities.
• Explore various programming language options, ranging from C to drag-and-drop interfaces.
• Test, debug, and deploy Arduino solutions to address real-world challenges.

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, IoT, automotive systems, AI acceleration, and server-grade processors. Industry analyses highlight a pressing talent deficit: with fewer than 5,000 RISC-V chip designers worldwide compared to an estimated 15,000+ open roles in the semiconductor sector. Current hiring trends indicate that employers are seeking candidates who combine proficiency in RISC-V architecture with skills in SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust 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. Organizations such as SiFive, Qualcomm, and Western Digital are accelerating their RISC-V initiatives, thereby increasing the demand for engineers capable of integrating architecture specification, silicon implementation, firmware, and software stack development within a unified skill set.