Online Microcontroller Training in Australia

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

Upon completing this training, participants will be able to:

• Grasp the fundamentals of TinyML and its advantages for edge AI applications.
• Configure a development environment suitable for TinyML projects.
• Train, optimise, and deploy AI models on low-power microcontrollers.
• Utilise TensorFlow Lite and Edge Impulse to build real-world TinyML applications.
• Optimise AI models for power efficiency and memory limitations.

This instructor-led, live training in Australia (online or on-site) 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 Australia, participants will learn how to program the Arduino for real-world applications, such as controlling lights, motors, and motion detection sensors. This course assumes the use of physical hardware components within a live laboratory environment, rather than software-simulated hardware.

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

• Program the Arduino to control lights, motors, and other devices.
• Understand Arduino's architecture, including inputs and connectors for add-on devices.
• Integrate third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to extend the 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 evolved from a niche open-source ISA into a mainstream architecture with significant market 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 against an estimated 15,000+ open positions in the semiconductor industry. Key hiring trends show employers prioritising 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.