Microcontroller Design Training Course

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

In this instructor-led, live training in Norway, 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 actual hardware components in a live lab environment, rather than software-simulated hardware.

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

• Program the Arduino to control lights, motors, and other devices.
• Understand the 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 programming language options, ranging from C to drag-and-drop languages.
• Test, debug, and deploy the Arduino to solve real-world problems.

This instructor-led, live training held in Norway (online or onsite) targets intermediate-level embedded systems engineers and AI developers who aim to deploy machine learning models on microcontrollers utilizing TensorFlow Lite and Edge Impulse.

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

• Grasp the core principles of TinyML and its advantages for edge AI solutions.
• Establish a development environment suitable for TinyML initiatives.
• Training, refining, and deploying AI models on power-efficient microcontrollers.
• Utilizing TensorFlow Lite and Edge Impulse to build practical TinyML applications.
• Enhancing AI models for improved power efficiency and to navigate memory limitations.

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

In this guided live training, participants will learn how to configure and code the Raspberry Pi to function as an interactive and robust embedded system.

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

• Configure an IDE (integrated development environment) to optimize development productivity
• Code the Raspberry Pi to manage devices such as motion sensors, alarms, web servers, and printers.
• Comprehend the Raspberry Pi's architecture, including input methods and connectors for expansion devices.
• Evaluate various programming languages and operating system options.
• Test, debug, and deploy the Raspberry Pi to address real-world challenges.

Audience

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

Course Format

• Blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• The Raspberry Pi is compatible with multiple operating systems and programming languages. This course utilizes the Linux-based Raspbian operating system and Python as the programming language. For specific setup requirements, please contact us to make arrangements.
• Participants are responsible for acquiring the necessary Raspberry Pi hardware and components.

This instructor-led, live training in Norway (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.