Course · 4 chapters
IA no Dispositivo e na 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
- 1IA On-Device & Edge: Comece Aqui
Uma orientação de 12 minutos sobre o skill path de IA On-Device & Edge — as três plataformas onde seu modelo pode rodar sem uma ida e volta à nuvem, e como escolher a sua.
- 2Apple Foundation Models para Desenvolvedores Swift
Coloque um LLM ~3B funcional dentro do seu app iOS — geração guiada, chamada de ferramentas e quando ainda faz sentido usar o Claude
- 3Gemini Nano e AICore no Android
Entregue IA on-device para mais de 140M de dispositivos Android — AICore como serviço compartilhado do sistema, APIs ML Kit GenAI e inteligência agêntica do Gemma 4.
- 4MLX na Prática: Inferência Local no Apple Silicon
Rode modelos abertos no seu Mac — memória unificada, quantização que realmente preserva qualidade, e os limites reais de um nó de inferência 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.