Modules
Take single modules or the whole track. Two hour sessions, combined into half days where it suits your calendar.
What AI Really Is
A plain language guide to AI assistants and how they differ from search and software.
- How large language models actually work, in plain language
- Where assistants fit against search, automation and traditional software
- First hands-on conversation with a real assistant
- Setting realistic expectations for what AI can and cannot do
Using AI Responsibly at Work
Build the guardrails and verification habits that keep AI use safe and on policy.
- When to reach for AI and when not to
- Guardrails, data care and the verification habit
- Applying your organisation's AI usage policy in practice
- Spotting confident-but-wrong output before it causes harm
Everyday AI Use Cases
Practical hands-on use of AI for writing, summarising, research and brainstorming.
- Drafting, editing and summarising real work documents
- Research and question answering with sensible verification
- Brainstorming and structured problem solving
- Turning a rough idea into a usable first draft fast
Connecting AI to Your Tools
Wire AI into the tools your team already lives in and share reusable workflows.
- Connecting assistants to email, chat, drives and apps
- Building reusable prompts and shared workflows
- Shared projects and prompt libraries for a team
- Keeping a consistent approach across the whole team
Teams Often Pair This With
Related modules other teams add alongside this track.
Critical Thinking With AI
Where human judgement still beats the machine, and why cognitive bias matters.
View module Applied AI Engineering · Prompt EngineeringHow LLMs Work for Builders
The mental model developers need: capabilities, context windows and model choice.
View module Applied AI Engineering · Prompt EngineeringStructured Outputs and Reliability
Get dependable JSON, Markdown and XML out of a model and manage hallucination.
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