Microcontroller Design Training Course

This instructor-led, live training in Bulgaria (online or onsite) 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 Bulgaria, participants will learn how to program Arduino for practical applications, such as controlling lights, motors, and motion detection sensors. This course requires the use of actual hardware components within a live laboratory setting, rather than relying on software-simulated hardware.

Upon completion of this training, participants will be able to:

• Program Arduino to control lights, motors, and other peripheral devices.
• Gain a comprehensive understanding of Arduino's architecture, including its inputs and connectors for expanding functionality with add-on devices.
• Integrate third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to enhance Arduino's capabilities.
• Evaluate various programming language options, ranging from traditional C to visual drag-and-drop environments.
• Test, debug, and deploy Arduino solutions to address real-world challenges.

This instructor-led, live training in Bulgaria (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 completion 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 solutions.
• Enhance AI models for better power efficiency and memory utilization.

The Raspberry Pi is a compact, single-board computer.

In this instructor-led live training session, participants will learn how to configure and program the Raspberry Pi to function as an interactive and potent embedded system.

Upon completion of this training, participants will be able to:

• Establish an IDE (integrated development environment) to maximize development productivity
• Program the Raspberry Pi to manage devices such as motion sensors, alarms, web servers, and printers.
• Comprehend the Raspberry Pi's architecture, including its inputs and connectors for add-on devices.
• Explore the diverse options available in programming languages and operating systems.
• Test, debug, and deploy the Raspberry Pi to address real-world problems.

Audience

• Developers
• Hardware/software technicians
• Technical professionals across all industries
• Hobbyists

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice.

Note

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

This instructor-led, live training in Bulgaria (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.

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

• Install TensorFlow Lite.
• Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
• Add AI to hardware devices without relying on network connectivity.