Current

Intermediate

Machine Learning at the Edge on Arm

edX · Arm Education · Updated March 2026

Platform rating

4.7/5

AI Tutor Rating

8.7/10

Duration

6 weeks

Classes

20

Deploy ML models on Arm-based edge devices. Learn TensorFlow Lite, model optimization, and real-time inference on embedded systems.

What you'll get

Deploy ML models on Arm edge devices

Optimize models with TensorFlow Lite

Build real-time inference pipelines

Design embedded ML applications

Course Curriculum

4 chapters

Fit

Best for

Autonomy Engineers

Self-Driving Developers

IoT Engineers

Systems Engineers

Not ideal for

Learners seeking only entry-level overviews

Prerequisites & pricing

Prerequisites

Basic ML and Python knowledge

Pricing

Free (verified: $149)

Certification

Certificate

Growth Leverage: Completing this course opens the door to roles such as Machine Learning Engineer, Edge AI Developer, or IoT Solutions Architect. Additionally, it positions individuals for certifications like the TensorFlow Developer Certificate, enhancing career advancement in the growing field of edge AI applications.

Skills Value: Employers pay a premium for skills in deploying ML models on edge devices, with salaries for Edge AI roles averaging 15-25% higher than traditional data science positions. This course equips learners to solve real-world challenges in real-time data processing and optimize resource-constrained environments.

Edge AI

Arm

TensorFlow Lite

Embedded

IoT

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