Foundations Line
Plain-language grounding in how modern AI works, what large language models are good at, where they fail, and how to use them safely on day one.
Beginner6–8 hours7 stationsFree
Who it's for: Anyone who uses a computer at work and wants to understand what AI can and cannot do before relying on it.
What you'll be able to do
- Explain in two sentences how a language model produces an answer
- Pick the right kind of AI tool for a task
- Spot the three most common failure modes: invented facts, stale knowledge, and overconfidence
- Write a first useful prompt and improve it with feedback
The route
Station 1: What AI is (and isn't)
Separate machine learning, deep learning and generative AI, and see why today's assistants feel conversational without being conscious.
Station 2: How language models predict text
Tokens, context windows and next-token prediction, explained with a paper-and-pencil example you can repeat for a colleague.
Station 3: Strengths and blind spots
Where models are reliably strong (drafting, summarising, reformatting) and where they need checking (numbers, citations, recent events).
Station 4: Your first ten prompts
A guided set of everyday tasks with before-and-after prompts so you feel the difference that context makes.
Station 5: Checking AI output
A five-question verification habit that catches most errors before they reach a client or manager.
Station 6: Privacy at work
What not to paste into a public chatbot, how enterprise plans differ, and how to read a data-use policy quickly.
Station 7: Choosing your toolkit
A simple decision table for assistants, search-style tools, image tools and AI features already inside your software.
Read along
- What is generative AI? A plain-English guide for working people · 8 min
- How large language models work: tokens, training and prediction · 10 min
- AI hallucinations: a five-question habit for catching errors · 8 min
- Using AI at work without leaking sensitive data · 8 min
Watch along
But what is a neural network?
3Blue1Brown · Build with AI
A visual first look at neurons, layers and weights. The clearest starting point for intuition.
Intro to Large Language Models
Andrej Karpathy · Foundations
A one-hour talk on what LLMs are, how they're trained, and where they're heading.
Introduction to Generative AI
Google Cloud Tech · Foundations
A short overview of generative AI concepts and terminology.
How to complete this line
Work through one station per sitting. For each: read the linked guide, watch the video where one is listed, then apply the idea to one real task from your own work and note the result. When you have done all stations, try the matching brief in this month's prompt challenge.