Online Microcontroller Training in Slovakia

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

Upon completing this training, participants will be able to:

• Grasp the core principles 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.
• Leverage TensorFlow Lite and Edge Impulse to build real-world TinyML solutions.
• Optimize AI models to meet power efficiency and memory constraints.

This instructor-led, live training in Slovakia (online or onsite) is designed for engineers who wish to learn how to utilize 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 Slovakia, participants will learn how to program 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 dominant architecture with substantial market traction in edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry analyses highlight a significant talent gap: there are fewer than 5,000 RISC-V chip designers worldwide, yet an estimated 15,000 or more positions remain open in the semiconductor industry. Current hiring trends indicate that employers value proficiency in RISC-V architecture combined with skills in System-on-Chip (SoC) design, RTL verification using UVM/SystemVerilog, AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain expertise. The fastest-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, fueling demand for engineers who possess a unified skill set spanning architecture specification, silicon implementation, firmware, and software stack development.