Microcontroller Training in Ostrava

This instructor-led, live training in Ostrava (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 completing this training, participants will be able to:

• Grasp the core concepts of TinyML and understand its advantages for edge AI applications.
• Establish 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.
• Optimize AI models to meet power efficiency and memory limitations.

This instructor-led, live training in Ostrava (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 Ostrava, participants will learn how to program Arduino for practical applications, such as controlling 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 architectural force, gaining substantial 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, while an estimated 15,000 or more positions in the semiconductor sector remain unfilled. Current hiring patterns reveal that employers prioritize candidates who possess deep proficiency in RISC-V architecture combined with expertise in System-on-Chip (SoC) design, RTL verification (using UVM and SystemVerilog), AI accelerator development, systems programming in Rust, confidential computing, and open-source toolchain management. The fastest-growing skill areas include automotive-grade RISC-V implementations (ISO 26262 compliance), server-class processors featuring Advanced Interrupt Controllers (AIA) and multi-core coherence, as well as Neural Processing Units (NPUs) for edge AI inference. Major companies such as SiFive, Qualcomm, and Western Digital are accelerating their RISC-V initiatives, creating a surge in demand for engineers capable of seamlessly integrating architecture specifications, silicon implementation, firmware development, and software stack engineering.