Choose with understanding
Read a model card, distinguish open weights from open source, and choose a model that fits your task and computer.
CyberCorps.uk · Practical AI
Artificial Intelligence: Open Weight Models
Run a language model on your own computer. Learn what open weights give you, get started with Ollama, and build a small assistant whose answers you can test.
- Guided lessons
- 8
- Suggested study time
- 3–4 hours
- Starting level
- Beginner
Choose your operating system
Eight lessons in each version, with setup, commands, and troubleshooting for your computer.
What you will be able to do
Run models locally
Install Ollama, pull a model, chat in the terminal, and manage downloaded and running models.
Build a repeatable workflow
Use the local API and a Modelfile to turn a useful prompt into a reusable assistant.
Evaluate the result
Test factual accuracy, uncertainty, and instruction following with a small, documented evaluation set.
Before you begin
- Use a Windows, macOS, or Linux computer where you can install software and open a terminal. The lessons guide you through your own local setup.
- Have internet access for the installer and model downloads, plus free disk space and memory for the model you choose. Lesson 3 explains how to check its requirements.
- Start with the small text model
gemma3:1b. It is a learning example; evaluate its answers carefully. - Use the supplied fictional notes for practice. You will need Python 3 for the API client and final project; the examples use its standard library with no extra packages.
Each lesson includes a practical task, a success checklist, and a knowledge check. Keep your prompts, settings, and observations in a learning log as you work.
Your learning path
From first model to working assistant
Work through the lessons in order, or return to a topic when you need a refresher.
Lesson 1 · 20 minutes
Understand open weight models
Understand weights, inference, licences, and the difference between local and cloud execution.
Open lesson →Lesson 2 · 25 minutes
Install Ollama and check your setup
Prepare your computer and verify that your local Ollama service is ready.
Open lesson →Lesson 3 · 25 minutes
Choose and run your first model
Download a small model, start a chat, and inspect the model running on your computer.
Open lesson →Lesson 4 · 25 minutes
Prompt clearly and evaluate answers
Ground answers in supplied notes and test accuracy, format, and uncertainty with repeatable prompts.
Open lesson →Lesson 5 · 30 minutes
Use the local Ollama API
Send chat requests from your terminal and Python, then read and validate the response.
Open lesson →Lesson 6 · 25 minutes
Create a reusable model with a Modelfile
Package a system instruction and generation settings into a named local assistant.
Open lesson →Lesson 7 · 25 minutes
Manage models, memory, and privacy
Inspect resource use, troubleshoot common problems, and keep local inference under your control.
Open lesson →Lesson 8 · 35 minutes
Build and assess a local study assistant
Bring the course together in a small project with evidence, evaluation, and a clear handover.
Open lesson →
Keep the essentials close
Find the main Ollama commands, a local API request, and the terms used throughout the course.