Course · 4 chapters

On-Device & Edge AI

Run AI directly on a phone or Mac with no cloud round-trip. Build with Apple Foundation Models, Gemini Nano, and MLX across 4 advanced chapters for app engineers.

Paidadvanced4 chapters78 minEnglish + 6 languagesCertificate on completion

What you'll be able to do

  • Embed Apple Foundation Models in iOS apps
  • Ship on-device AI to Android with Gemini Nano
  • Run local models on Apple Silicon with MLX
  • Choose on-device or cloud inference
  • Match edge platforms to your use case

What's inside

  1. 1
    On-device en edge AI: begin hier

    Een oriëntatie van 12 minuten op het leerpad on-device en edge AI — de drie platforms waar je model kan draaien zonder rondje langs de cloud, en hoe je het juiste kiest.

    12 min
  2. 2
    Apple Foundation Models voor Swift-ontwikkelaars

    Ship een capabel ~3B LLM in je iOS-app — guided generation, tool calling, en wanneer je toch voor Claude kiest

    22 min
  3. 3
    Gemini Nano en AICore op Android

    Lever on-device AI aan 140M+ Android-apparaten — AICore als gedeelde systeemservice, ML Kit GenAI-API's en Gemma 4 agentische intelligentie.

    22 min
  4. 4
    MLX in de Praktijk: Lokale Inferentie op Apple Silicon

    Draai willekeurige open modellen op je Mac — unified memory, kwantisatie die daadwerkelijk kwaliteit behoudt, en de eerlijke limieten van een single-user inferentie-node

    22 min

Frequently asked questions

What will I learn in this on-device AI course?
You learn to run AI models directly on a device with no cloud call, using Apple Foundation Models in iOS apps, Gemini Nano and AICore on Android, and MLX for local inference on Apple Silicon. The path also covers quantization, tool calling, and when to fall back to a cloud model like Claude.
Who is this course for?
It is built for software and AI engineers, especially iOS, Android, and Mac developers who want to add private, low-latency AI features that work without a server. The level is advanced and assumes you already ship production app code.
Do I need coding experience to take this course?
Yes. This is an advanced engineering path that works with Swift on iOS, Android system APIs, and Python tooling such as MLX and Ollama, so you should already be comfortable building and running app code.
How long is the course and is there a certificate?
The path has 4 chapters totaling about 78 minutes, with a 12-minute orientation and three 22-minute platform chapters on Apple, Android, and Mac. You earn a certificate of completion after finishing every chapter.
Is this course free?
No, On-Device & Edge AI is a paid path included in the AI Academy subscription. It sits in the AI for Engineers track alongside the other AI engineering paths.

Earn a certificate

Complete all chapters to receive your certificate of completion.