Professional Courses

Fundamentals of TinyML (Online), Harvard University

Master TinyML, Machine Learning, and Deep Learning Online at Harvard

Written By : Srinivas
Reviewed By : Sankha Ghosh

Harvard School of Engineering and Applied Sciences offers Fundamentals of TinyML as an introductory online course through its partnership with edX. The course introduces learners to the basics of Machine Learning, Deep Learning, and embedded systems for tiny devices such as smartphones. Participants develop essential skills in data collection, model training, and embedded ML applications, preparing them for advanced TinyML courses.

What You’ll Learn in This Course?

This course enables learners to:

  • Understand fundamentals of Machine Learning and Deep Learning algorithms.

  • Gather and prepare data for training ML models.

  • Train and deploy ML models on tiny devices and embedded systems.

  • Explore embedded ML concepts and their applications in smartphones and small devices.

  • Learn Responsible AI design principles for TinyML applications.

Accessibility and Value

This 100% online, self-paced course requires 2–4 hours per week, making it flexible for learners worldwide. Free access is available to all, with an optional paid certification. It’s designed for beginners and AI enthusiasts, providing foundational TinyML knowledge without prior Machine Learning or embedded systems experience.

Comprehensive Curriculum

  • Foundations of Machine Learning: Learn ML algorithms, model training, and computational logic.

  • Deep Learning Fundamentals: Understand neural networks and their use in TinyML.

  • Data Collection for ML: Techniques to gather, clean, and prepare datasets.

  • Embedded Machine Learning: Apply ML models to tiny devices and integrate with hardware.

  • Responsible AI Design: Explore ethical considerations in embedded AI systems.

  • Practical Applications: Work on projects to apply TinyML concepts in real-world scenarios.

Eligibility Criteria

  • No prior Machine Learning or Deep Learning knowledge required.

  • Basic computer skills a sufficient.

  • Suitable for beginners, AI enthusiasts, and those interested in embedded systems.

What Makes This Course Stand Out?

The course provides hands-on exposure to TinyML at the intersection of software and hardware. Learners work with tiny devices to deploy ML models and gain practical understanding of embedded AI. It serves as the foundation for the TinyML Professional Certificate program.

Final Thoughts

Fundamentals of TinyML equips learners with core ML and DL concepts for tiny devices. The course provides practical experience and prepares participants for more advanced TinyML applications in AI and embedded systems.

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