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
