Microcontroller Training in San Pedro Garza Garcia

This instructor-led, live training in San Pedro Garza Garcia (online or onsite) targets intermediate-level embedded systems engineers and AI developers seeking to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

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

• Understand the core principles of TinyML and its benefits for edge AI applications.
• Establish a development environment for TinyML initiatives.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Use TensorFlow Lite and Edge Impulse to create real-world TinyML applications.
• Optimize AI models for power efficiency and memory limitations.

This instructor-led, live training in San Pedro Garza Garcia (online or onsite) is designed for engineers looking to master embedded C programming for various microcontrollers across different processor architectures, including 8051, ARM CORTEX M-3, and ARM9.

In this instructor-led, live training in San Pedro Garza Garcia, 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 real hardware components within a live lab environment (rather than 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 its inputs and connectors for add-on devices.
• Integrate third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to extend Arduino's functionality.
• Understand the various programming language options available, ranging from C to drag-and-drop interfaces.
• Test, debug, and deploy Arduino solutions to address real-world problems.

The RISC-V ecosystem has evolved from a niche open-source Instruction Set Architecture (ISA) into a mainstream architectural choice, gaining significant momentum across edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry reports highlight a critical talent gap: there are fewer than 5,000 RISC-V chip designers globally compared to an estimated 15,000+ open positions in the semiconductor industry. Current hiring trends indicate that employers prioritize proficiency in RISC-V architecture combined with System-on-Chip (SoC) design, RTL verification (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 (AIA interrupt controllers, multi-core coherence), and edge AI inference NPUs. Companies such as SiFive, Qualcomm, and Western Digital have accelerated their RISC-V development efforts, driving demand for engineers capable of bridging architecture specification, silicon implementation, firmware, and software stack development within a single skill set.