Current

Intermediate

AI on Jetson: Building Real-Time AI Applications

NVIDIA Deep Learning Institute (DLI) · NVIDIA · Updated March 2026

Platform rating

4.7/5

Champ rating

8.7/10

Duration

8 hours self-paced

Classes

24

Build real-time AI applications on NVIDIA Jetson edge devices. Cover deployment, optimization, and computer vision at the edge.

What you'll get

Deploy AI models on Jetson edge devices

Build real-time computer vision pipelines

Optimize inference for edge hardware

Create IoT-connected AI 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 Python and Linux

Pricing

Free

Certification

Certificate

Jetson

Edge AI

Computer Vision

IoT

NVIDIA

ShareCompare

Add to StackGo to Course

Alternatives to AI on Jetson: Building Real-Time AI Applications

Compare

Current

Machine Learning at the Edge on Arm

edX · Arm Education

4.7

8.7/10

6 weeks

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

Free (verified: $149)

ViewAddCompare

Deploy machine learning on edge devices and microcontrollers. Learn computer vision, anomaly detection, and MLOps for embedded AI.

Learn the fundamentals of deploying AI on edge devices including model optimization, MLOps for edge, and IoT integration.

Deploy machine learning on microcontrollers from Harvard University covering TinyML, edge inference, and ML model deployment on resource-constrained devices.