Arduino Programming for Beginners Training Course

This instructor-led, live training session, delivered either virtually or in person, is designed for technical personnel seeking to acquire proficiency in using Embedded C to program diverse microcontroller platforms, including those based on 8051, ARM CORTEX M-3, and ARM9 architectures.

This instructor-led live training in US (available online or on-site) targets intermediate-level embedded systems engineers and AI developers aiming to implement machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse for government operations.

Upon completion of this training, participants will demonstrate the ability to:

• Explain the core principles of TinyML and its operational advantages in edge AI contexts.
• Configure and manage a development environment suitable for TinyML initiatives.
• Train, refine, and implement AI models on low-power microcontrollers.
• Leverage TensorFlow Lite and Edge Impulse to develop practical TinyML solutions for government use cases.
• Enhance AI model performance regarding power efficiency and memory limitations.

The RISC-V ecosystem has evolved from a specialized open-source instruction set architecture to a mainstream platform demonstrating significant market momentum across edge computing, IoT, automotive, AI acceleration, and server-class processor domains. Industry analyses indicate a critical talent shortage: fewer than 5,000 RISC-V chip designers are currently active globally, contrasted against an estimated 15,000+ open positions within the semiconductor sector. Key hiring trends reveal that employers prioritize RISC-V architecture proficiency combined with SoC design, RTL verification (UVM/SystemVerilog), AI accelerator development, Rust systems programming, confidential computing, and open-source toolchain expertise. The expansion of automotive-grade RISC-V implementations (ISO 26262), server-class processors (AIA interrupt controllers, multi-core coherence), and edge AI inference NPUs represents the fastest-growing competency areas. Organizations including SiFive, Qualcomm, and Western Digital have accelerated RISC-V development, driving demand for engineers capable of bridging architecture specification, silicon implementation, firmware, and software stack development within a unified skill set for government and public sector applications.