8 programmes. 24 modules.

Explain data as a managed asset

Describe ownership and stewardship

Apply quality and privacy basics

Stand up governance and a council

Appoint and enable stewards

Define standards and resolve issues

Design the analytics function

Advance the method portfolio

Track and realise value

Build one trusted source of metrics

Design decision-grade dashboards

Enable governed self-service

Explain AI, ML and generative AI

Identify and prioritise use cases

Apply responsible-AI basics

Build an AI inventory and risk tiers

Operate AI approval and oversight

Apply RAI reviews and controls

Explain LLMs and their limits

Design effective, safe prompts

Apply acceptable-use and controls

Set AI strategy linked to value

Oversee AI risk and responsibility

Drive adoption and value realisation