Microcontroller Training in Varna

This instructor-led, live training in Varna (online or onsite) is designed for intermediate-level embedded systems engineers and AI developers looking 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 suitable 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.
• Enhance AI models for better power efficiency and memory utilization.

This instructor-led, live training in Varna (online or onsite) is aimed at engineers who wish to learn how to use embedded C to program various types of microcontrollers based on different processor architectures (8051, ARM CORTEX M-3, and ARM9).

In this instructor-led live training in Varna, 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 actual hardware components within a live laboratory setting, rather than relying on software-simulated hardware.

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

• Program Arduino to control lights, motors, and other peripheral devices.
• Gain a comprehensive understanding of Arduino's architecture, including its inputs and connectors for expanding functionality with add-on devices.
• Integrate third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to enhance Arduino's capabilities.
• Evaluate various programming language options, ranging from traditional C to visual drag-and-drop environments.
• 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 traction across edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry reports highlight a pressing talent deficit: with fewer than 5,000 RISC-V chip designers globally and over 15,000 open positions in the semiconductor sector, there is a clear supply gap. Current hiring trends indicate that employers prioritize candidates proficient in RISC-V architecture, alongside skills in SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain management. The fastest-growing competency 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 development, intensifying the demand for engineers capable of bridging architecture specification, silicon implementation, firmware, and software stack development within a unified skill set.