Embedded System Programme Training Course

This instructor-led, live training in Taiwan (online or on-site) is designed for engineers seeking to master embedded C programming for a variety of microcontrollers across different processor architectures, including 8051, ARM CORTEX M-3, and ARM9.

In this instructor-led live training in Taiwan, participants will learn how to program Arduino for real-world 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.

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

• Program Arduino to control lights, motors, and other devices.
• Gain a solid understanding of Arduino's architecture, including inputs and connectors for add-on devices.
• Integrate third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to expand Arduino's functionality.
• Understand the various programming language options available, ranging from C to drag-and-drop languages.
• Test, debug, and deploy Arduino solutions to address real-world problems.

This instructor-led, live training in Taiwan (online or onsite) is designed for engineers and computer scientists who wish to apply the fundamentals of circuits and electronics to design devices and systems that utilize the properties of electrical components for developing hardware functionalities.

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

• Set up and configure the necessary tools and programs for circuits and circuit board development.
• Understand the basic principles behind circuits and electronics engineering.
• Utilize primary electronic components to construct efficient computer hardware technologies.
• Optimize electronic devices by implementing circuit analysis methods.
• Apply the fundamentals of electronics and circuits to the development of enterprise applications.

This instructor-led live training in Taiwan (online or onsite) is tailored for engineers and scientists who wish to learn and apply DSP implementations to efficiently handle different signal types and gain better control over multi-channel electronic systems.

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

• Set up and configure the necessary software platform and tools for Digital Signal Processing.
• Understand the concepts and principles that are foundational to DSP and its applications.
• Familiarize themselves with DSP components and employ them in electronics systems.
• Generate algorithms and operational functions using the results from DSP.
• Utilize the basic features of DSP software platforms and design signal filters.
• Synthesize DSP simulations and implement various types of filters for DSP.

This two-day course delves into essential design principles, supported by practical code examples and the latest industrial technologies, providing significant value to automotive software developers.

This instructor-led, live training (available online or onsite) is designed for C developers who want to learn embedded C design principles.

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

• Understand the design considerations that make embedded C programs reliable
• Define the functionality of an embedded system
• Define the program logic and structure to obtain the desired result
• Design a reliable, error-free embedded application
• Obtain optimal performance from target hardware

Format of the Course:

• Interactive lecture and discussion
• Exercises and practice
• Hands-on implementation in a live-lab environment

Course Customization Options:

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level automotive engineers and technicians who wish to gain hands-on experience in testing, simulating, and diagnosing ECUs using Vector tools like CANoe and CANape.

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

• Understand the role and function of ECUs in automotive systems.
• Set up and configure Vector tools such as CANoe and CANape.
• Simulate and test ECU communication on CAN and LIN networks.
• Analyze data and perform diagnostics on ECUs.
• Create test cases and automate testing workflows.
• Calibrate and optimize ECUs using practical approaches.

This instructor-led live training Taiwan (online or onsite) is designed for intermediate automotive engineers and embedded systems developers who wish to grasp the theoretical aspects of ECUs, emphasizing Vector-based tools and methodologies used in automotive design and development.

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

• Understand the architecture and functions of ECUs in modern vehicles.
• Analyze communication protocols used in ECU development.
• Explore Vector-based tools and their theoretical applications.
• Apply model-based development principles to ECU design.

In this instructor-led live training, participants will learn how to code using FreeRTOS by stepping through the development of a simple RTOS project on a microcontroller.

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

• Understand the fundamental concepts of real-time operating systems.
• Learn about the FreeRTOS environment.
• Acquire skills in coding with FreeRTOS.
• Interface a FreeRTOS application with hardware peripherals.

This instructor-led live training in Taiwan (online or onsite) is tailored for FPGA developers who wish to utilize Vivado for designing, debugging, and implementing hardware solutions.

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

• Develop HDL systems with C code and Vivado tools.
• Generate and implement soft processors in Vivado.
• Test and simulate C code using Vivado.

This instructor-led, live training session at Taiwan (online or onsite) targets intermediate-level embedded systems engineers and AI developers who want to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of TinyML and its advantages for edge AI applications.
• Configure a development environment tailored for TinyML projects.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Leverage TensorFlow Lite and Edge Impulse to build real-world TinyML solutions.
• Enhance AI models for power efficiency and address memory constraints.

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

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

In this instructor-led live training, participants will learn how to configure and program 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 maximize development productivity
• Program the Raspberry Pi to control devices such as motion sensors, alarms, web servers, and printers
• Understand the Raspberry Pi's architecture, including inputs and connectors for add-on devices
• Understand the 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 persons in all industries
• Hobbyists

Format of the course

• Part lecture, part discussion, exercises and heavy 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 Taiwan (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.