HARVARD UNIVERSITY · UNITED STATES
Fundamentals of TinyML
Certificate · Taught in en
At a glance
1 mo
Duration
—
IELTS
€0k
Tuition / yr
en
Language
Certificate
Level
- Learn from Harvard facultyFaculty
- Flexible self-paced learningPace
- Earn a certificate upon completionCertification
- Contribute to the Harvard global communityCommunity
This online course introduces the fundamentals of TinyML (Tiny Machine Learning), a rapidly growing area within Deep Learning. TinyML bridges the gap between embedded systems, like smartphones, and machine learning applications. It requires expertise in both software and hardware. You will learn essential data science techniques for collecting data and gain an understanding of algorithms to train basic machine learning models. Upon completion, you will understand the core concepts of TinyML and be prepared for more advanced topics. This course is the first in the TinyML Certificate series. While it provides an introduction, it is not a mandatory prerequisite for the subsequent 'Applications of TinyML' and 'Deploying TinyML' courses if you already possess sufficient experience in machine learning and embedded systems. The course is delivered through edX, enabling a global community of learners to participate.
Frequently asked questions
- What is the cost of the Verified Certificate for the Fundamentals of TinyML course?
- The Verified Certificate costs $299 USD. This fee grants full access to all course materials, activities, tests, and forums, and allows you to receive a certificate upon passing.
- How can I pay the tuition fees for the Verified Certificate?
- Payment can be made via e-checks, paper checks (drawn on a US bank), credit/debit cards (MasterCard, Visa, American Express, Discover), or through TransferMate for international payments.
- What are the entry requirements for the Fundamentals of TinyML course?
- No specific academic or English language requirements are listed for this individual course, as it is designed to be accessible to learners interested in the field.
- How do I enroll in the Fundamentals of TinyML course?
- You can enroll via the edX platform. Choose between a free audit option or the Verified Certificate option, which requires payment of $299 USD.
- What is the language of instruction for this course?
- The course is delivered online via edX and the primary language of instruction and materials is English.
- What are the career prospects after completing this course?
- This course provides foundational knowledge in TinyML, applicable to roles in embedded AI development, IoT engineering, and machine learning specialization, though it is not a direct career placement service.
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Fees
Tuition (international)A Verified Certificate costs $299 USD. This price provides full access to course materials, activities, tests, and forums. Learners who pass the course can receive a certificate. An audit option is available for free, offering access to select course materials.
Tuition (home)A Verified Certificate costs $299 USD. This price provides full access to course materials, activities, tests, and forums. Learners who pass the course can receive a certificate. An audit option is available for free, offering access to select course materials.
Living—
Payment can be made via e-checks, paper checks (drawn on a US bank), credit/debit cards (MasterCard, Visa, American Express, Discover), or through TransferMate for international payments. Payment is due by a specified deadline, and late payments may result in course drops.
How to apply
1. Visit the edX PlatformNavigate to the edX course page for 'Fundamentals of TinyML' by Harvard University.
2. Choose Your Enrollment OptionSelect either the 'Audit' option to access course materials for free (without a certificate) or the 'Verified Certificate' option to gain full access and receive a certificate upon successful completion.
3. Enroll and Pay (for Verified Certificate)If choosing the Verified Certificate, proceed with the enrollment process and make the payment of $299 USD. Payment options include credit/debit cards or potentially other methods supported by edX. For international payments, TransferMate may be an option, though specific details for edX enrollments would need to be confirmed on the edX platform.
4. Access Course MaterialsOnce enrolled, you will gain access to the course content, including lectures, readings, activities, and assessments.
5. Complete the CourseWork through the course materials at your own pace, adhering to the weekly time commitment of 2-4 hours. Complete all required assignments and assessments to earn a passing grade.
6. Receive Your CertificateUpon successfully passing the course, your Verified Certificate will be issued.
Accreditation
The course is offered by Harvard University, and upon successful completion, learners receive a Verified Certificate from HarvardX.
Frequently asked questions
What is the cost of the Verified Certificate for the Fundamentals of TinyML course?
+
The Verified Certificate costs $299 USD. This fee grants full access to all course materials, activities, tests, and forums, and allows you to receive a certificate upon passing.
How can I pay the tuition fees for the Verified Certificate?
+
Payment can be made via e-checks, paper checks (drawn on a US bank), credit/debit cards (MasterCard, Visa, American Express, Discover), or through TransferMate for international payments.
What are the entry requirements for the Fundamentals of TinyML course?
+
No specific academic or English language requirements are listed for this individual course, as it is designed to be accessible to learners interested in the field.
How do I enroll in the Fundamentals of TinyML course?
+
You can enroll via the edX platform. Choose between a free audit option or the Verified Certificate option, which requires payment of $299 USD.
What is the language of instruction for this course?
+
The course is delivered online via edX and the primary language of instruction and materials is English.
What are the career prospects after completing this course?
+
This course provides foundational knowledge in TinyML, applicable to roles in embedded AI development, IoT engineering, and machine learning specialization, though it is not a direct career placement service.