Microcontroller Design Training Course

This instructor-led, live training in US (online or onsite) is designed for engineers who seek to acquire the skills necessary to utilize embedded C for programming a variety of microcontrollers based on different processor architectures, including 8051, ARM Cortex-M3, and ARM9. The training aligns with professional development goals for government and industry professionals, ensuring participants gain practical knowledge that can be directly applied to enhance technical capabilities in their respective fields.

In this instructor-led, live training for government participants, attendees will learn how to program the Arduino for practical 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 various devices, including lights and motors. - 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 enhance Arduino's capabilities. - Explore the different programming language options available, from C to drag-and-drop languages. - Test, debug, and deploy Arduino solutions to address real-world challenges.

This course provides an in-depth examination of modern C language standards (C99, C11, C2x) with a focus on their application in embedded systems programming. It emphasizes efficient and error-resistant coding practices essential for government projects. Practical examples and exercises are conducted using STM32 family microcontrollers to ensure hands-on experience and real-world applicability.

This instructor-led, live training (online or onsite) is designed for intermediate-level embedded systems engineers and AI developers who are interested in deploying machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse for government applications. 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 suitable for TinyML projects. - Train, optimize, and deploy AI models on low-power microcontrollers. - Utilize TensorFlow Lite and Edge Impulse to implement practical TinyML applications. - Optimize AI models to meet power efficiency and memory constraints.

The Raspberry Pi is a compact, single-board computer designed for versatile applications.

In this instructor-led, live training, participants will learn how to configure and program the Raspberry Pi to function as an interactive and powerful embedded system suitable for government use.

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

• Set up an Integrated Development Environment (IDE) to maximize development efficiency
• Program the Raspberry Pi to control devices such as motion sensors, alarms, web servers, and printers
• Understand the architecture of the Raspberry Pi, including its inputs and connectors for add-on devices
• Explore various options in programming languages and operating systems suitable for government applications
• Test, debug, and deploy the Raspberry Pi to address real-world challenges

Audience

• Developers
• Hardware and software technicians
• Technical personnel from all sectors, including government agencies
• Hobbyists interested in government applications

Format of the Course

• Part lecture, part discussion, with exercises and extensive hands-on practice

Note

• The Raspberry Pi supports various operating systems and programming languages. This course will use Linux-based Raspbian as the operating system and Python as the programming language. For a specific setup, please contact us to arrange.
• Participants are responsible for purchasing the necessary Raspberry Pi hardware and components.

This instructor-led, live training in US (online or onsite) is aimed at engineers who wish to develop, deploy, and execute machine learning models on very small embedded devices for government use.

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

• Install TensorFlow Lite for government applications.
• Load machine learning models onto an embedded device to enable it to perform tasks such as speech detection and image classification without network connectivity.
• Incorporate artificial intelligence into hardware devices to enhance functionality and efficiency in public sector workflows.

This course provides an overview of common serial interfaces utilized in embedded systems, along with practical details for their implementation. Participants will engage in hands-on exercises utilizing STM32 microcontrollers, enhancing their skills and knowledge for government applications.

This course provides an overview of fundamental aspects of USB device programming and the practical application of STM32CubeIDE for developing USB device firmware. It is designed to enhance technical skills and align with best practices for government projects, ensuring efficient and secure development processes.