Online Microcontroller Training in Uzbekistan

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

Upon completing this training, participants will be capable of:

• Grasping the core principles of TinyML and its advantages for edge AI solutions.
• Configuring a development environment suitable for TinyML initiatives.
• Training, optimizing, and deploying AI models on power-efficient microcontrollers.
• Leveraging TensorFlow Lite and Edge Impulse to create practical TinyML applications.
• Enhancing AI models for improved power efficiency and adherence to memory limitations.

This instructor-led, live training in Uzbekistan (online or onsite) is designed for engineers who want to learn how to use 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 Uzbekistan, participants will learn how to program Arduino for real-world applications, such as controlling lights, motors, and motion detection sensors. This course focuses on using 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 manage lights, motors, and other devices.
• Understand Arduino's architecture, including its inputs and connectors for add-on devices.
• Integrate third-party components like LCDs, accelerometers, gyroscopes, and GPS trackers to enhance Arduino's capabilities.
• Explore various programming language options, from C to drag-and-drop languages.
• Test, debug, and deploy Arduino to address real-world challenges.

The RISC-V ecosystem has evolved from a niche open-source Instruction Set Architecture (ISA) into a mainstream architecture with significant momentum across edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry reports highlight a critical talent shortage: there are fewer than 5,000 RISC-V chip designers globally, while the semiconductor industry has an estimated demand for over 15,000 positions. Key hiring trends indicate that employers prioritize proficiency in RISC-V architecture combined with SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain skills. 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 have accelerated RISC-V development, driving demand for engineers who can bridge architecture specification, silicon implementation, firmware, and software stack development within a single skill set.