Not all machine learning is deployed to large clusters; many of our everyday devices like smartwatches and smart thermostats run ML models on low-power embedded computers. The Graduate Certificate in Tiny Machine Learning prepares students to develop and deploy machine learning models for use on embedded systems that use data from on-board sensors and other sources. Students consider tradeoffs in model accuracy, computational power, and energy usage along with security and reliability concerns.
All 8 credits can be applied towards the Master's in Machine Learning and can be completed in two semesters.
| Mode of Delivery | Program Credits | Required Admissions Documents |
| Online synchronous (two nights a week, 2-hour live lecture) | 8 credits |
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