What Will You Learn?
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
About This Course
Provider: Edx
Format: Online
Duration: 20 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: At the end of this course, you will be able to understand the “language” behind TinyML and be ready to dive into the application of TinyML in future courses.
Course Prerequisites: Basic Scripting in Python
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Harvard University
Key Topics: Data Collection, Machine Learning Algorithms, Deep Learning, Embedded Systems, Algorithms, Smartphone Operation, Data Science, Machine Learning
Topic Covered:
- - Welcome to TinyML
- - Course Overview
- - The Future of ML is Tiny and Bright
- - TinyML Challenges
- - Getting Started
- - Introduction to (Tiny) ML
- - The Machine Learning Paradigm
- - The Building Blocks of Deep Learning
- - Exploring Machine Learning Scenarios
- - Building a Computer Vision Model
- - Responsible AI Design
- - Summary
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