Generative AI Advanced
Prompting, applied use cases, and leading an organisation through adoption
About this course
The follow-on to the primer, and a different kind of course: less about what generative AI is and more about prompting it well, applying it to a real case study, and leading a team or organisation through adoption without the usual damage.
The largest block is applied — a domain case study the participants have to actually solve using generative AI, rather than watch being solved. The closing modules are about strategy, workforce skills, use-case prioritisation, risk mitigation and the change management that decides whether any of it lands.
Case studies and examples are drawn from your own industry, so the applied work is about problems you recognise.
What you’ll be able to do
- Explain what generative AI model architectures do at a level sufficient to make build-versus-buy and hosting decisions
- Design prompts deliberately: structure, constraints, examples, and an evaluation of whether the prompt is actually working
- Solve a domain case study end to end using generative AI, and present the reasoning as well as the result
- Apply generative AI to strategy, planning, performance management, market research and decision-making, with the limits stated
- Discover, prioritise and convert business problems into AI problems, and assess whether the organisation is ready
- Lead adoption: workforce skills, productivity claims that survive scrutiny, risk mitigation and change management
Before you start
What this course assumes you can already do.
- The Generative AI Primer, or equivalent working familiarity with what a large language model does and gets wrong.
- Comfortable using a general-purpose AI assistant for real work already.
- For the strategy modules: enough context on your own organisation to name real processes and owners.
The curriculum
Open any module to see its objective, every teaching topic, the practice brief and the checkpoint.
Recaps and reference material are included in the LMS.
PART 1Models and prompting
01Generative AI Models
Understand generative model architecture well enough to make the decisions a leader actually faces — hosted or self-hosted, general or specialised, what a context window costs you — without needing to train anything.
- Introduction to generative AI modelsConcept
- Generative AI architectureConcept
Write the hosting decision for one use case
Take one candidate use case and write the model decision: a hosted API or a self-hosted open-weight model, general-purpose or specialised. Argue it on data sensitivity, cost, latency and who has to maintain it.
Knowledge checkpoint with explained answers
02Prompt Engineering
Stop guessing at prompts. Design them from a structure, constrain them deliberately, and test whether a change actually improved anything instead of assuming it did.
- Introduction to prompt engineeringConcept
- Effective prompt designHands-on
- Generating and testing effective promptsHands-on
Improve a prompt and prove it improved
Take one prompt you already use for real work. Build a small test set for it, then change it deliberately and measure whether the change helped.
Knowledge checkpoint with explained answers
PART 2Applied work
03Use Cases and Applied Learning
Solve a real case study from your own domain using generative AI, and be able to defend the approach — including the parts where the technology was the wrong tool.
- Generative AI use cases in your domainConcept
- Applied case study: solve a domain problem with generative AIHands-on
Solve the case study and show your reasoning
Work the domain case study through to a result using generative AI. The assessed artefact is not the output but the reasoning trail: what you tried, what failed, and where you decided the technology was not the right tool.
Knowledge checkpoint with explained answers
PART 3Strategy and leadership
04Applying AI for Business Value Creation
Use generative AI on the work leaders actually do — strategy, planning, performance management, market research — and know which of those outputs can be trusted and which need a human check before they leave the room.
- AI for strategy, planning, performance and decisionsConcept
- Evolving skills and work practices for AI at workConcept
Use AI on a leadership task, then audit it
Pick one genuine leadership task — a planning document, a market scan, a performance review structure — and do it with AI assistance. Then audit the output as if you were the person it would affect.
Knowledge checkpoint with explained answers
05Leading in an AI Driven World
Lead adoption with evidence: a current view of the landscape, productivity claims that survive scrutiny, a use-case pipeline with a prioritisation rule, a risk position, and a change approach that accounts for how people actually respond.
- The current generative AI landscapeConcept
- Increasing workforce productivity with generative AIConcept
- Generative AI applications in your domainConcept
- Mitigating risk and ensuring responsible useConcept
- Discovering and prioritising AI use casesHands-on
- Building an AI-first culture: change managementConcept
Build the use-case pipeline and the risk position
Assemble a real pipeline of candidate use cases for your own organisation, apply a prioritisation rule you can defend, and write the risk and change position that would have to accompany the top one.
Knowledge checkpoint with explained answers
Domain case study plus an adoption position
Two joined halves: solve a case study in your own domain with generative AI, then write the adoption position that would have to accompany rolling it out. The case-study brief is matched to your industry.
Model and hosting decision — Decide what you will build on, and defend it.
A tested prompt system — Prompts with an evaluation set, not prompts that felt right.
The domain case study — Solve it, and show the reasoning including the failures.
Applied to leadership work — Use it on the work leaders do, and audit what comes out.
The adoption position — The document that decides whether any of this survives contact with the organisation.
Next course
Tell us about yourself or your team and we’ll let you know how and when you can take this course.