Applications of TinyML
2-4 hours per week • Start today
Individual Course
Course Length
7 weeks
2-4 hours per week
Featuring faculty from:
Harvard John A. Paulson School of Engineering and Applied Sciences
Enroll as Individual
Certificate Price:
$ 299
Enroll as Individual
Certificate Price:
$ 299
Understand Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning).
Are you ready to scale your (tiny) machine learning application? Do you have the infrastructure in place to grow? Do you know what resources you need to take your product from a proof-of-concept algorithm on a device to a substantial business Machine Learning (ML) is more than just technology and an algorithm; it's about deployment, consistent feedback, and optimization. Today, more than 87% of data science projects never make it into production. To support organizations in coming up to speed faster in this critical domain it is essential to understand Machine Learning Operations (MLOps). This course introduces you to MLOps through the lens of TinyML (Tiny Machine Learning) to help you deploy and monitor your applications responsibly at scale. MLOps is a systematic way of approaching Machine Learning from a business perspective. This course will teach you to consider the operational concerns around Machine Learning deployment, such as automating the deployment and maintenance of a (tiny) Machine Learning application at scale. In addition, you’ll learn about relevant advanced concepts including neural architecture search, allowing you to optimize your models' architectures automatically; federated learning, allowing your devices to learn from each other; and benchmarking, enabling you to performance test your hardware before pushing the models into production. This course focuses on MLOps for TinyML (Tiny Machine Learning) systems, revealing the unique challenges for TinyML deployments. Through real-world examples, you will learn how tiny devices, such as Google Homes or smartphones, are deployed and updated once they’re with the end consumer, experiencing the complete product life cycle instead of just laboratory examples. Are you ready for a billion users? The course will be delivered via edX and connect learners around the world.
Self-Guided
edX
Know why and when deploying MLOps can help your (tiny) product or business.
Key MLOps platform features that you can deploy for your data science project.
Real-world examples and case studies of MLOps Platforms targeting tiny device.
Your Instructor
Associate Professor at John A. Paulson, School of Engineering and Applied Sciences (SEAS) at Harvard University
Vijay Janapa Reddi is an Associate Professor at Harvard University, Inference Co-chair for MLPerf, and a founding member of MLCommons, a nonprofit ML (Machine Learning) organization aiming to accelerate ML innovation.
These courses can be bundled together to receive a Professional Certificate at a discounted price.
Learn More2-4 hours per week • Start today
2-4 hours per week • Start today
Ways to take this course
A Verified Certificate costs $299 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate.
Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums. Please note that this track does not offer a certificate for learners who earn a passing grade.
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