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By request

Government AI Programme

A scoped training format for public-sector teams that need safe, reviewable AI workflows.

Beginner to team-readyScoped cohortPublic-sector teams
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01 / OVERVIEW

What this programme is

The Government AI Programme adapts the Academy learning spine for teams that need cautious, reviewable use of AI in public-service contexts.

The emphasis is on safe use, controlled examples, clear review checkpoints, and human judgement. Exercises use sample, public, sanitized, or approved data only.

02 / WHO IT IS FOR

Built for the right context

  • Teams exploring practical AI literacy for public-service work.
  • Officers who need safer drafting, summarising, research, and briefing habits.
  • Groups that need a training brief scoped before delivery.

03 / OBJECTIVES

What learners should leave with

  • Map appropriate and inappropriate AI use cases.
  • Draft reviewable prompts and outputs for routine work.
  • Build a simple workflow map with human checkpoints.
  • Review public-facing or internal sample outputs before use.

04 / MODULE OUTLINE

Seven modules, summary only

M-01

AI Basics

Understand what AI can and cannot do before using it for real work.

  • Common AI uses
  • Human judgement
  • Safe first tasks
Safe-use checklist
M-02

Prompting

Give clearer instructions and review the result instead of accepting the first answer.

  • Prompt structure
  • Context and constraints
  • Review loops
Reusable prompt template
M-03

Workflows

Break a repeated task into steps where AI can help without taking over.

  • Task mapping
  • Drafting support
  • Human checkpoints
Workflow map
M-04

Research

Use AI to explore and compare information while checking sources and missing context.

  • Question framing
  • Source comparison
  • Briefing notes
One-page comparison brief
M-05

Build Practice

Turn the learning into a visible output, prototype, worksheet, tracker, or build-lab path.

  • Output selection
  • Build planning
  • First useful draft
Practical build artifact
M-06

Review And Safety

Check AI output for mistakes, privacy risk, weak claims, tone issues, and missing review.

  • Accuracy checks
  • Privacy awareness
  • Share-readiness review
Review checklist
M-07

Final Project

Package one useful result and explain what was made, how it was checked, and what comes next.

  • Project story
  • Evidence of work
  • Next improvement
Final project story

05 / DELIVERY

How it runs

  • Delivered by request after scope, audience, and data boundaries are agreed.
  • Exercises avoid private or sensitive data unless formally approved by the organisation.
  • Outputs are treated as training artifacts, not production systems.

06 / NEXT ACTION

Review the path, then choose the right next step.

Public pages stay at overview level. Academy learning surfaces hold the actual lessons, labs, and resources.

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