Course · 4 chapters
AI on-device ed edge
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.
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
- 1On-Device & Edge AI: parti da qui
Un orientamento di 12 minuti allo percorso On-Device & Edge AI — le tre piattaforme dove il tuo modello può girare senza round-trip cloud, e come scegliere la tua.
- 2Apple Foundation Models per sviluppatori Swift
Porta un LLM ~3B capace dentro la tua app iOS — guided generation, tool calling e quando conviene comunque ricorrere a Claude
- 3Gemini Nano e AICore su Android
Porta l'AI on-device su 140M+ dispositivi Android — AICore come system service condiviso, le API ML Kit GenAI e l'intelligenza agentica di Gemma 4.
- 4MLX in pratica: inferenza locale su Apple Silicon
Fai girare modelli aperti arbitrari sul tuo Mac — memoria unificata, quantization che mantiene davvero la qualità e i limiti onesti di un nodo di inferenza single-user
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.