Online Microcontroller Training in Nigeria

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

By the end of 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, optimize, and deploy AI models on low-power microcontrollers.
• Utilize TensorFlow Lite and Edge Impulse to build real-world TinyML applications.
• Optimize AI models to meet power efficiency and memory constraints.

This instructor-led, live training in Nigeria (online or onsite) is designed for engineers who want to learn how to use embedded C to program various microcontrollers based on different processor architectures (8051, ARM CORTEX M-3, and ARM9).

In this instructor-led live training in Nigeria, participants will learn how to program Arduino for real-world applications, such as controlling lights, motors, and motion detection sensors. This course assumes the use of actual hardware components in a live lab environment (not 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 inputs and connectors for add-on devices.
• Add 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 specialized open-source instruction set architecture (ISA) into a dominant mainstream architecture, gaining significant traction in edge computing, the Internet of Things (IoT), automotive sectors, AI acceleration, and server-class processors. Industry analyses highlight a pressing shortage of skilled professionals: with fewer than 5,000 RISC-V chip designers worldwide, there are over 15,000 open positions in the semiconductor industry. Current hiring trends indicate that employers are prioritizing candidates who possess proficiency in RISC-V architecture alongside skills in System-on-Chip (SoC) design, RTL verification using UVM and SystemVerilog, AI accelerator development, Rust systems programming, confidential computing, and experience with open-source toolchains. The most rapidly growing 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. Tech giants such as SiFive, Qualcomm, and Western Digital are accelerating their RISC-V development efforts, creating intense demand for engineers capable of seamlessly bridging architecture specification, silicon implementation, firmware, and software stack development within a unified skill set.