Small steps. Useful skills.

See what you can do.

A question becomes a plan. Rough notes become a clear next step. You don’t need to understand computers or artificial intelligence to get started. You’re in the right place.

Try the 5-minute AI exercise

Ask AI what to pack for a day at the park. Then try a follow-up question.

Choose a starting point These are sample results. Your AI’s answer may be different.

START WITH THE BASICS

You ask

What should I bring to the park?

AI suggests

Water, a snack, a hat, sunscreen, and a blanket.

I’ve never used AI

Show me how to ask my first question.

Let’s try it BUILD A LITTLE CONFIDENCE

Before · rough notes

We need water and snacks for Saturday. Check the weather, too.

After · sample result

Pack water
Bring snacks
Check the weather

I’ve tried AI a little

Give me something useful to practice.

Let’s try it TRY AN EVERYDAY TASK

Before · rough notes

Team meeting: Jo checks the supplies Friday. Sam books the room Monday.

After · sample result

Jo: check supplies by Friday
Sam: book room by Monday

I want to use AI for work

Show me practical everyday examples.

Let’s try it

Video 45 SecondsOne question. About five minutes. Go at your own pace.

AI words, in plain language

A short guide to 15 terms. You do not need to memorize them to get started.

Read and copy the AI glossary

Copy the glossary and paste it into your notes or a document to save it. You can also select and copy the text directly.

AI Practice Lab · AI words, in plain language

Artificial intelligence (AI): Computer systems that perform tasks such as recognizing patterns, working with language, or making predictions.
Generative AI: AI that creates content, such as text, pictures, audio, or video.
Chatbot: A program you talk with through messages. Some chatbots use generative AI.
Prompt: The question, instructions, or information you give an AI tool.
Follow-up: Another message that adds details, asks a question, or requests a change.
Context: The information available to the AI for its current response, such as instructions and parts of the conversation.
Model: The trained mathematical system that an AI tool uses to produce results.
Training: The process of adjusting a model using examples or other feedback. An ordinary chat does not necessarily retrain the model.
Token: A small unit a model uses to process information. In text, it may be part of a word, a whole word, or punctuation.
Large language model (LLM): A model trained on large amounts of text to work with language, including generating responses.
Hallucination: An AI response that includes invented or incorrect information, even when it sounds confident.
Bias: Patterns that can lead an AI system to treat people or ideas unfairly or give a one-sided result.
Verification: Checking a result against reliable sources or real-world evidence before relying on it.
Automation: Using software or machines to carry out steps with less hands-on work.
AI agent: An AI system that can use tools and take steps toward a goal. Its actions and permissions still need human oversight.