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Running AI Locally: Private LLMs with Ollama and Open Models

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  • Why and How to Run AI Locally
    Local AI vs Cloud AI: Privacy, Cost and Control Trade-offs 14m ! Choosing Your Hardware: CPU, GPU, RAM and Realistic Expectations 16m ! Installing Ollama and Running Your First Local Model 18m !
  • Working with Open-Source Models
    Understanding Model Sizes, Quantization and GGUF Formats 17m ! Comparing Popular Open Models for Different Use Cases 16m ! Running a Local Chat Interface with LM Studio and Open WebUI 18m !
  • Building with Local Models
    Calling Local Models via API for Your Own Apps 19m ! Connecting Local LLMs to n8n and Automation Workflows 20m ! Retrieval-Augmented Generation with Local Embeddings 21m !
  • Going Further, Safely and Reliably
    Fine-Tuning vs Prompting: What Actually Makes Sense Locally 15m ! [Activite pratique] Build a Private Local Assistant for a Real Task 25m ! [Evaluation courte] Local AI Readiness Self-Check 12m !

Building with Local Models

This module moves from chatting with a local model to actually building with it: calling it from code, connecting it to automations and grounding it in your own data.

These are the skills that turn a local model into a real tool.
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