Microcontroller Training in Oslo

This instructor-led, live training in Oslo (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 Oslo (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 Oslo, participants will learn how to program the Arduino for real-world usage, such as to control lights, motors and motion detection sensors. This course assumes the use of real 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.

This instructor-led, live training in Oslo (online or onsite) is aimed at engineers who wish to learn the design principles of microcontroller design.

Raspberry Pi is a compact, single-board computer.

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

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

• Set up an integrated development environment (IDE) for optimal productivity
• 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
• Test, debug, and deploy the Raspberry Pi to solve real-world problems

Audience

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

Format of the course

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

Note

• 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. To request a specific setup, please contact us to arrange.
• Participants are responsible for purchasing the Raspberry Pi hardware and components.

This instructor-led, live training in Oslo (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.