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AI FUNDAMENTALS

Run Ollama On Your Own Machine

Run powerful AI models on your machine - no API costs, complete privacy

Build it
Run Ollama On Your Own Machine project preview
Ollama

Difficulty

Beginner

Time to complete

45 minutes

Availability

Free

BUILD

What you'll build

Set up Ollama to run AI models locally on your computer. Learn local AI fundamentals, create custom personas, and build without cloud dependencies or API costs.

1. Install Ollama Service

Download and install Ollama, configure the local server, and verify it runs on your system.

2. Pull Your First Model

Download the qwen2.5 AI model from Ollama library and verify the installation with a list command.

3. Chat with Local AI

Start an interactive session with your AI model and test responses using the terminal interface.

4. Understand AI Limitations

Discover what local models can and cannot do, and learn about RAG for custom data access.

5. Create Custom Persona

Build a specialized AI assistant using Modelfiles and system prompts without retraining models.

Your portfolio builds as you work.

Every project documents itself as you go. Finish the work, and your proof is ready to share.

PROJECT

Real world application

Skills you'll learn

  • Terminal Commands

    Execute CLI commands to manage services and interact with AI

  • Local AI Infrastructure

    Set up and run AI models on your own hardware

  • Model Management

    Pull, list, and organize AI models from registries

  • Configuration Skills

    Create Modelfiles and customize AI behavior with prompts

  • AI Fundamentals

    Understand parameters, context windows, and model capabilities

  • Privacy-First Computing

    Run AI without internet, API keys, or data leaving your machine

Tech stack

  • Ollama logo

    Ollama

    Open-source tool for running large language models locally with simple terminal commands.

OUTCOME

Where this leads.

Relevant Jobs

Roles where these skills matter:

  • AI Engineer
  • Machine Learning Engineer
  • Backend Developer
  • Full Stack Developer

Build a RAG API with FastAPI

Create an AI-powered API that answers questions using your own documents with retrieval-augmented generation.

Build a RAG API with FastAPI

Continue the Journey

FAQs

Everything you need to know

No coding required! This project uses basic terminal commands that we explain step-by-step. If you can copy and paste, you can complete this.

Completely free. Ollama is open-source, and all models are free to download and use. Unlike cloud AI services like OpenAI or Anthropic, there are no API costs or subscriptions.

This project uses qwen2.5:0.5b, a tiny model that runs on any modern computer with 8GB RAM. Larger models (7b, 13b, 70b) require more memory and ideally a GPU for faster responses.

No, you can jump right in!

Local AI gives you complete privacy (no data sent to companies), zero API costs, offline capability, and full control. Perfect for sensitive data, experimentation, or building products without vendor lock-in.

RAG (Retrieval-Augmented Generation) is a technique that gives AI models access to your own documents and data. Local models don't know about you or your files, so RAG solves that limitation. You'll learn RAG in the next project.

One Project. Real Skills.

45 minutes from now, you'll have completed Run Ollama On Your Own Machine. No prior experience needed. Just step-by-step guidance and a real project for your portfolio.

Let's Build This

Beginner-friendly