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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf StudyVideo and Text Based

Course Overview

The Fundamentals of TinyML Training Course is an open course provided on the HarvardX platform coordinated by edX and Harvard University. The course will introduce students to the fundamentals of embedded systems and machine learning along with the core aspects of TinyML language.

The Fundamentals of TinyML Certification Syllabus will benefit students who are interested in data analysis and statistics. The course is an introductory level course that requires students to have knowledge about basic scripting techniques in Python. The course is supported by online study materials and instructed by Vijay Janapa Reddi and Laurence Moroney.

The Fundamentals of TinyML Course is taught over 5 weeks in a self-paced manner. The course focuses on the main aspects of deep learning, machine learning, and embedded devices and systems, like smartphones and other devices. Upon the successful completion of the online exams and assignments, students will receive a certificate if they choose the verified mode with the course fee. In the free mode, they can audit it for a limited period. 

The Highlights

  • Shareable certificate upon completion
  • Self-paced course 
  • 5 weeks duration
  • 2 to 4 hours weekly study
  • English medium
  • Online course materials
  • Graded assignments and exams
  • Knowledge of TinyML

Programme Offerings

  • Shareable Certificate upon completion
  • Self-paced Course
  • 5 Weeks Duration
  • 2 to 4 Hours Weekly Study
  • English medium
  • Online Course Materials
  • Graded Assignments and Exams

Courses and Certificate Fees

Fees InformationsCertificate AvailabilityCertificate Providing Authority
INR 24964yesHarvard University, Cambridge

The course allows students to choose between two options. The free version of the course will provide only limited access to study materials. In order to get unlimited course materials along with the opportunity to attend exams, and assignments and gain a certificate, students should enroll in the paid course. The paid course fee is Rs. 24,964  only.

Fundamentals of TinyML Course Fee Structure

Course

Amount in INR

Fundamentals of TinyML

Rs. 24,964 /-


What you will learn

Machine learningKnowledge of deep learningData science knowledgeKnowledge of Artificial Intelligence

After completing the Fundamentals of TinyML Training Course, you will learn about the following topics:

  • Fundamentals of Machine Learning (ML)
  • Fundamentals of Deep Learning
  • How to gather data for ML
  • How to train and deploy ML models
  • Understanding embedded ML
  • Responsible AI Design

Admission Details

Given below are the steps to enroll in the Fundamentals of TinyML Online Course:

Step 1: Click on the URL given below -

https://www.edx.org/course/fundamentals-of-tinyml

Step 2: Click on the enroll option in the course description.

Step 3: When the tap opens, enter your name, email id, and password and create a new account.

Step 4: Once your account is created you can choose the course name and enroll.

The Syllabus

  • Chapter 1: Welcome to TinyML
  • Chapter 1.1: Course Overview
  • Chapter 1.2: The Future of ML is Tiny and Bright
  • Chapter 1.3: TinyML Challenges
  • Chapter 1.4: Getting Started
  • Chapter 2: Introduction to (Tiny) ML
  • Chapter 2.1: The Machine Learning Paradigm
  • Chapter 2.2: The Building Blocks of Deep Learning
  • Chapter 2.3: Exploring Machine Learning Scenarios
  • Chapter 2.4: Building a Computer Vision Model
  • Chapter 2.5: Responsible AI Design
  • Chapter 2.6: Summary

Instructors

Harvard University, Cambridge Frequently Asked Questions (FAQ's)

1: Will I get unlimited access to online course materials?

Yes, students who join the paid course will get access to unlimited course materials.

2: Is the course certificate I receive shareable?

Yes, the certificate of completion given to the students is shareable.

3: In how many weeks can I complete the online course?

The Fundamentals of the TinyML Training Course can be completed within 5 weeks.

4: Can I attend the course in my own time?

Yes, it is a self-paced course that allows students to progress at their own speed.

5: What is the number of weekly study hours required for the course?

The course would require 2 to 4 study hours per week from the students.

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