Online Microcontroller Training in Guatemala

This instructor-led, live training in Guatemala (online or onsite) is aimed at intermediate-level embedded systems engineers and AI developers who wish to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

By the end of this training, participants will be able to:

• Understand the fundamentals of TinyML and its benefits for edge AI applications.
• Set up a development environment for TinyML projects.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Use TensorFlow Lite and Edge Impulse to implement real-world TinyML applications.
• Optimize AI models for power efficiency and memory constraints.

This instructor-led, live training in Guatemala (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 Guatemala, participants will learn how to program the 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 matured from a niche open-source ISA to a mainstream architecture with significant market momentum across edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry reports identify a critical talent shortage: fewer than 5,000 RISC-V chip designers exist globally against an estimated 15,000+ open positions in the semiconductor industry. Key hiring trends show employers prioritizing RISC-V architecture proficiency paired with SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain skills. The rise of automotive-grade RISC-V (ISO 26262), server-class processors (AIA interrupt controllers, multi-core coherence), and edge AI inference NPUs represents the fastest-growing competency areas. Companies including 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 in a single skill set.