Location Tag: Singapore

EdgeAI System for Industry 4.0 applications and beyond (Batch 4)

Industry 4.0 brings about transformational changes to the manufacturing landscape, from productivity, operational efficiency to quality control. These smart factories are deploying IoT sensors and devices to collect huge amount of data via cloud computing, equipped with AI analytics tools, to derive useful production insights.

This course covers fundamental concepts of edge AI technology and how it is being deployed for real-life industrial applications related to I4.0 and beyond.

Learning objectives:

At the end of the programme, you would be able to:

  • Explain the basics of neural network training
  • Describe how ANN and CNN machine learning works
  • Apply deep learning training for supervised learning in object classification
  • Explain the basics of Edge AI Platform and Applications
  • Describe how VitisAI and Model Zoo for machine learning works
  • Explain the components of Edge AI Board Hardware
  • Utilise linux script to run an AI programme on the EdgeAI board

Course Prerequisites:

Learners are expected to be able to:

  • Have basic know-how on electronics to make sense of the course.
  • Own and have basic knowledge of operating a computer
  • Must be able to run command shell

Course fee:

This is a course under the SkillsFuture series for Singapore Citizens (SC) and Singapore Permanent Residents (PR). The course fees is inclusive of venue and course materials. Certificate of participation will be provided for participants who have attended 75% of the course.

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Machine Learning at the Edge with Microchip Microcontrollers – SAMD21 ML Kit

In today’s AI-driven world, Machine Learning and Deep Learning have become essential technologies. But how can you easily grasp their concepts and leverage them effectively? This comprehensive course will provide you with a solid understanding of machine learning principles, as well as practical skills in deploying trained neural networks on microcontrollers—a field known as embedded machine learning or TinyML.

Designed with beginners in mind, this course will take you from the fundamentals to designing and implementing your own machine learning-enabled projects on SAMD21G18 Arm® Cortex®-M0+ based MCU. This course provides step by-step guide for deploying Edge Impulse Studio project onto a Microchip Arm® Cortex®-based 32-bit microcontroller on the SAMD21 ML Kit with the MPLAB® X IDE.

Hands-on exercises will help you gain proficiency in preparing data, developing and testing machine learning models, and deploying them to real physical hardware, the SAMD21 ML Kit and using a user-friendly graphical programming tool of MPLAB® X & Edge Impulse.

Learning objectives:

At the end of the programme, you would be able to:

  • Define the basics of a machine learning system and explain the key processes involved.
  • Train, test, deploy and adjust deep neural network models specifically tailored for SAMD21G18 Arm® Cortex®-M0+ core based
    microcontrollers.
  • Interpret machine learning information to make informed decisions and perform accurate predictions within embedded systems.
  • Recall areas of knowledge expansion in AI and machine learning.

Course Prerequisites:

Learners are expected to be able to:

  • Learners are required to read/write and speak at WPLN 4 or an equivalent level.
  • Learners are to be proficient in operating a computer.
  • Learners are to bring their own laptops/computers (no admin rights) for the hands-on exercises.
  • Installation of application software and its dependencies
  • *These must be running Windows OS (Windows 8.1 and above) as IOS and Macbooks and other OS are not supported.

Course fee:

S$88 (inclusive of  SAMD21 ML Kit)

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Machine Learning at the Edge with ADI Microcontroller MAX78000 – Enabling True Low Power Edge Inference

In today’s AI-driven world, Machine Learning and Deep Learning have become essential technologies. But how can you easily grasp their concepts and leverage them effectively? This comprehensive course will provide you with a solid understanding of machine learning principles, as well as practical skills in deploying trained neural networks on microcontrollers—a field known as embedded machine learning or TinyML.

Designed with beginners in mind, this course will take you from the fundamentals to designing and implementing your own machine learning-enabled projects on Arm Cortex-M4 100MHz processor with FPU and RISC-V core, 32-bit RISC-V coprocessor and come with Convolution Neural Network Accelerator (CNN). This course provides a step-by-step guide for implementing and deploying artificial intelligence (AI) solutions onto an ADI MAX78000FTHR Development Board.

Hands-on exercises will help you gain proficiency in preparing data, developing and testing machine learning models, and deploying them to a real physical hardware, the MAX78000FTHR Development Board, and using the ai8x framework tools and Eclipse IDE in the process.

Learning objectives:

At the end of the programme, you would be able to:

  • Define the basics of a machine learning system and explain the key processes involved.
  • Train, test and deploy convolutional neural network models (CNN) specifically tailored for the MAX78000 microcontroller.
  • Interpret machine learning information to make informed decisions and perform accurate predictions within embedded systems.
  • Recall areas of knowledge expansion in AI and machine learning.

Course Prerequisites:

Learners are expected to be able to:

  • Learners are required to read/write and speak at WPLN 4 or an equivalent level.
  • Learners are to be proficient in operating a computer.
  • Learners are to bring their own laptops/computers (no admin rights) for the hands-on exercises.
  • Installation of application software and its dependencies
  • *These must be running Windows OS (Windows 10.0 and above) as IOS and Macbooks and other OS are not supported.

Course fee:

S$250 (inclusive of the MAX78000FTHR Development Board

 

Download Brochure

EdgeAI System for Industry 4.0 applications and beyond

Industry 4.0 brings about transformational changes to the manufacturing landscape, from productivity, operational efficiency to quality control. These smart factories are deploying IoT sensors and devices to collect huge amount of data via cloud computing, equipped with AI analytics tools, to derive useful production insights.

This course covers fundamental concepts of edge AI technology and how it is being deployed for real-life industrial applications related to I4.0 and beyond.

Learning objectives:

At the end of the programme, you would be able to:

  • Explain the basics of neural network training
  • Describe how ANN and CNN machine learning works
  • Apply deep learning training for supervised learning in object classification
  • Explain the basics of Edge AI Platform and Applications
  • Describe how VitisAI and Model Zoo for machine learning works
  • Explain the components of Edge AI Board Hardware
  • Utilise linux script to run an AI programme on the EdgeAI board

Course Prerequisites:

Learners are expected to be able to:

  • Have basic know-how on electronics to make sense of the course.
  • Own and have basic knowledge of operating a computer
  • Must be able to run command shell

Course fee:

This is a course under the SkillsFuture series for Singapore Citizens (SC) and Singapore Permanent Residents (PR). The course fees is inclusive of venue and course materials. Certificate of participation will be provided for participants who have attended 75% of the course.

Download Brochure
Register Now

EdgeAI System for Industry 4.0 applications and beyond

Industry 4.0 brings about transformational changes to the manufacturing landscape, from productivity, operational efficiency to quality control. These smart factories are deploying IoT sensors and devices like cameras on the factory floor to collect huge amount of data that is live streamed via cloud computing, equipped with AI analytics tools, to derive useful production insights. With the ever-increasing sensor deployment and big data collected, coupled with growing privacy and cyberattack risk concern, edge AI will overcome these challenges and offer more immense benefits to Industry 4.0 and beyond like facial and suspicious object recognition in security and surveillance, autonomous robots and drones in the healthcare and logistics sectors.

Learning objectives:

  • This course covers fundamental concepts of edge AI technology and how it is being deployed for real-life industrial applications related to I4.0 and beyond. It would reinforce its usefulness in providing real-time prediction, using structured data like manufactured product / facial image, to give participants a comprehensive insight into how best to adapt this methodology for their specific needs
  • Edge AI technology would reinforce its usefulness in providing real-time prediction and using structured data like manufactured product and facial image to give participants a comprehensive insigh into how best to adapt this methodology for their specific needs.

Course fee:

This is a course under the SkillsFuture series for Singapore Citizens (SC) and Singapore Permanent Residents (PR). The course fees is inclusive of venue and course materials. Certificate of participation will be provided for participants who have attended 75% of the course.

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