Curriculum · 5 levels · 18 modules open · 15 coming soon
Everything we teach. In the order that builds.
Five levels, from what AI is to running it across an organisation. 18 modules are open now, and the 15 marked “Coming soon” are next. Every fact in it is dated and re-checked, monthly at the least. The assessment decides where you start, so you never sit through what you already know.
Level I · Learn
Foundations
What AI is, where it came from, how it learns, and what it can't do.
About this level →Module 1What AI actually isAI, machine learning, deep learning and generative AI, untangled: what each term means, what it doesn't, and why the hype and the fear both miss.Module 2A short history of AIFrom Turing and the 1956 Dartmouth workshop through two AI winters, deep learning and the transformer to ChatGPT and agents: how we got here, and what it predicts.Module 3How machines learnData, training and prediction; supervised, unsupervised and reinforcement learning, explained with everyday examples and no maths.Module 4Types and styles of AINarrow and general, predictive and generative, rules and learning: the different styles of AI and where you already meet each one.Module 5Meet the modelsLanguage, image, speech and video models; open and closed; large and small; reasoning models: the kinds of model behind the tools, and who makes them.Module 6Your first conversations with AIGetting started with an AI assistant safely: what to ask, how to follow up, and how to tell a good answer from a confident one.Module 7Limitations and staying safeHallucination, bias, knowledge cutoffs, privacy, deepfakes and AI-powered scams: what AI gets wrong, and how to protect yourself.
Level II · Learn
Practitioner
Using AI well at work: prompting, checking, choosing tools and protecting data.
About this level →Module 8Prompting wellContext, examples, structure and iteration: how to ask for what you actually want, and get it the first or second time.Module 9AI for writing, research and analysisDrafting, summarising, researching and analysing data with AI, with the checking habits that keep your name safe on the result.Module 10AI for images, audio and videoGenerating and editing images, voice, music and video: what the tools can do, what they can't, and the rights questions to ask first.Module 11The Tool Atlas: choosing the right toolThe 32 tools that matter, from ChatGPT to n8n: what each is good at, what to watch out for, and how to judge any new one in five questions.Module 12Checking AI's workFact-checking, source-checking and spotting hallucinations: the habits that turn a fluent draft into something you can sign off.Module 13Data, privacy and your workplaceWhat not to paste, how UK GDPR applies, training settings in each tool, and working inside your organisation's AI policy.Module 14AI for small businessesPractical workflows for a small UK business: customer emails, quotes, marketing, admin and bookkeeping support, with realistic costs and risks.
Level III · Build
Builder
How models really work, and building with them: APIs, automation, agents.
About this level →Module 15How large language models workTokens, embeddings, attention, context windows, temperature and training: what is actually happening when a model answers you.
Module 16Training, fine-tuning and retrievalPre-training, fine-tuning and retrieval-augmented generation (RAG): which one solves which problem, and what each really costs.
Module 17Working with AI APIsKeys, models, tokens and costs, rate limits and caching: calling a model from your own code or no-code tool, safely.
Module 18Automation and no-code workflowsBuilding real workflows in Zapier, Make and n8n, with AI steps that summarise, classify and draft, and humans where they belong.
Module 19Agents and tool useWhat makes an agent, tool calling, MCP, agent loops and guardrails: building AI that takes actions, and keeping it on a short lead.
Module 20Evaluating AI systemsEvals, benchmarks and their limits, test sets and human review: how to know whether an AI system is good enough to ship.
Module 21AI securityPrompt injection, data leakage, jailbreaks and supply-chain risk: the new attack surface, from the defender's side.
Level IV · Grow
Leader
Leading AI in a team: use cases, business cases, policy and buying well.
About this level →Module 22Finding and prioritising use casesWhere AI genuinely helps a team, how to find those places, and how to choose what to do first without chasing hype.
Module 23Business cases and ROICosting AI honestly, measuring value, and writing a business case a finance director will believe.
Module 24Change, skills and shadow AIBringing people with you: skills, adoption, and the staff already using AI without telling anyone.
Module 25Responsible AIFairness, transparency, human oversight and accountability, turned into practical decisions rather than posters.
Module 26Writing an AI policyAn acceptable-use policy your team will actually follow: scope, approved tools, data rules, disclosure, and how to keep it current.Module 27Buying AIEvaluating vendors, contracts and data terms: the questions to ask before your organisation signs up to an AI product.
Level V · Grow
Director
Enterprise AI: strategy, architecture, governance, regulation and the board.
About this level →Module 28Enterprise AI strategy and operating modelsSetting an AI strategy, centres of excellence and hub-and-spoke models, and deciding what to centralise.
Module 29Architecture and platform choicesBuild, buy or partner; model portfolios; open and closed models; sovereignty; and the real cost of AI at scale.
Module 30Governance frameworksISO/IEC 42001, the NIST AI Risk Management Framework, model risk and internal controls: governance that stands up to audit.
Module 31AI regulation: the EU AI Act and the UK approachThe EU AI Act and its timeline, the UK's principles-based approach, UK GDPR and the regulators: what applies to your organisation, and when.Module 32Board reporting and AI riskAI risk registers, incident response and reporting to the board: what directors need to see, and how often.
Module 33Leading an AI-ready organisationCulture, capability and pace: leading an organisation that uses AI well, and keeps learning as it changes.
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