Course · 4 chapters
IA en Dispositivo y en el 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: Empieza aquí
Una orientación de 12 minutos al skill path de On-Device & Edge AI — las tres plataformas donde tu modelo puede ejecutarse sin un round-trip a la nube, y cómo elegir la tuya.
- 2Apple Foundation Models para desarrolladores Swift
Lanza un LLM de ~3B capaz dentro de tu app de iOS — generación guiada, llamada a herramientas y cuándo seguir recurriendo a Claude
- 3Gemini Nano y AICore en Android
Envía AI on-device a más de 140M dispositivos Android — AICore como servicio del sistema compartido, APIs de ML Kit GenAI, y inteligencia agéntica de Gemma 4.
- 4MLX en práctica: Inferencia local en Apple Silicon
Ejecuta modelos open arbitrarios en tu Mac — memoria unificada, cuantización que realmente preserva calidad, y los límites honestos de un nodo de inferencia de un solo usuario
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.