Online Microcontroller Training in South Africa

This instructor-led, live training in South Africa (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 South Africa (online or onsite) is designed for engineers who want to master embedded C programming for a range of microcontrollers across different processor architectures, including 8051, ARM CORTEX M-3, and ARM9.

In this instructor-led, live training in South Africa, participants will learn how to program the Arduino for practical applications, such as controlling lights, motors, and motion detection sensors. This course requires the use of real hardware components in a live lab environment (software-simulated hardware is not used).

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.
• Integrate 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 evolved from a niche open-source instruction set architecture (ISA) into a mainstream architectural choice, gaining substantial momentum across edge computing, IoT, automotive, AI acceleration, and server-class processors. Industry analyses highlight a significant talent gap: there are fewer than 5,000 RISC-V chip designers globally, contrasted against an estimated 15,000+ open positions within the semiconductor industry. Key recruitment trends indicate that employers are prioritising candidates who possess proficiency in RISC-V architecture alongside skills in 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 compliant), server-class processors (featuring AIA interrupt controllers and multi-core coherence), and edge AI inference NPUs. Leading companies such as SiFive, Qualcomm, and Western Digital have accelerated their RISC-V development efforts, thereby driving demand for engineers capable of bridging architecture specification, silicon implementation, firmware, and software stack development within a single skill set.