Arduino Programming for Beginners Training Course

This guided, live instruction delivered in US (online or onsite) is intended for engineers seeking proficiency in utilizing embedded C to develop applications for diverse microcontrollers across multiple processor architectures, including 8051, ARM CORTEX M-3, and ARM9. This curriculum is designed for government professionals requiring precise technical training standards.

This facilitated, instructor-led instruction provided in US (delivered online or at a designated site) targets intermediate-level embedded systems engineers and artificial intelligence developers seeking to implement machine learning models on microcontrollers through the use of TensorFlow Lite and Edge Impulse.

Upon completion of this curriculum, participants will be able to:

• Comprehend the core principles of TinyML and its advantages for edge artificial intelligence initiatives, particularly those relevant for government applications.
• Configure a suitable development environment for TinyML-based projects.
• Execute the training, optimization, and deployment of artificial intelligence models on low-power microcontroller hardware.
• Utilize TensorFlow Lite and Edge Impulse to construct practical TinyML solutions.
• Enhance artificial intelligence models for improved power efficiency and adherence to memory limitations.

The RISC-V ecosystem has evolved from a specialized open-source instruction set architecture into a dominant platform with substantial momentum in edge computing, IoT, automotive applications, AI acceleration, and server infrastructure. Current industry assessments highlight a significant workforce deficit, noting that fewer than 5,000 RISC-V chip designers are available globally to meet the estimated 15,000+ open roles within the semiconductor sector. Employment data indicates that organizations prioritize candidates with proficiency in RISC-V architecture alongside skills in SoC design, RTL verification using UVM/SystemVerilog, AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain management. The most rapidly expanding competency areas include automotive-grade RISC-V compliant with ISO 26262 standards, server-class processors featuring AIA interrupt controllers and multi-core coherence, and edge AI inference NPUs. Major firms such as SiFive, Qualcomm, and Western Digital are accelerating RISC-V initiatives, creating a heightened demand for engineers capable of integrating architecture specification, silicon implementation, firmware, and software stack development.