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AI Foundations
Module 101Track A — Foundations90 min

AI at Work 101

Beginners

People who have been handed an AI assistant at work, or are about to be, and want to know what it is before they trust it

Prerequisites: None. A laptop and access to any one of the four assistants, on any plan.

Last verified 2026-09-17

Learning objectives

By the end, participants can:

  1. Describe a large language model as next-word prediction at scale, and name two things that follow from it
  2. Recognise hallucination and sycophancy in an answer, and know the one habit that defuses each
  3. Explain tokens and context windows well enough to know why long chats degrade
  4. Tell the four surfaces apart (chat, desktop app, inside the office suite, agents) and pick the right one for a task
  5. Complete and iterate a first useful task on their own material, with any of the four assistants

What's in this module

7 lessons · 5 exercises · ~8 min reading

Starts withWhat a large language model is~1 min

Executive summary

You will learn what a large language model actually is, what that makes it good and bad at, and how the four assistants most organisations use (Claude by Anthropic, Gemini by Google, ChatGPT by OpenAI, and Microsoft 365 Copilot by Microsoft) package the same idea in different surfaces. End state is one real task from your own work completed with whichever assistant you have, iterated to something you would actually use. After this module you can explain hallucination and sycophancy to a colleague, tell a chat surface from an agent surface, write a first useful brief, and know when to start a new conversation instead of arguing with an old one.

Sources

Prefer the live room?

This module also runs inside our in-person bootcamps and workshops in Copenhagen.

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