Build the AI skills your role needs.

FOUNDATIONS — AI for Business Leaders. Explain AI capabilities and limitations, distinguish useful opportunities from unsuitable applications, and prioritise business problems. Produce an AI opportunity map. Entry course: AI for CXOs and Business Leaders.

PRACTITIONER — AI Strategy, Governance & Adoption (in development). Assess readiness, build a business case, define accountability and human oversight, and plan workforce adoption. Produce an AI strategy and governance plan.

ADVANCED — Leading Enterprise AI Transformation (in development). Prioritise an AI portfolio, design an operating model, assess suppliers and measure business value. Produce an executive investment brief and 90-day roadmap.

For executives, directors and heads of function. Outcome: lead AI adoption with clear objectives, ownership, controls and measurable value.

FOUNDATIONS — Practical AI for Product Professionals. Identify suitable customer problems, distinguish AI from conventional automation, and define users, tasks, evidence and boundaries. Produce a one-page Enterprise AI Solution Canvas. Entry course: AI for POs and BAs: From AI Idea to Buildable Product. PRACTITIONER — AI Product Discovery & Delivery (in development). Validate assumptions, prototype a solution, define data needs and create an AI-ready backlog with acceptance criteria. Produce a validated prototype and prioritised backlog. ADVANCED — AI Product Evaluation. Build evaluation datasets, assess quality, safety, cost and latency, and design release gates and feedback loops. Produce an evaluation scorecard and improvement roadmap. Related course: AI Evals for Product Owners and Business Analysts.

For Product Owners, Product Managers and Business Analysts. Outcome: own an AI product from discovery through evaluation and improvement. Choose an entry point based on your experience; stages describe progression, not mandatory prerequisites.

FOUNDATIONS — AI for Scrum Masters & Delivery Professionals (in development). Identify applications in planning, facilitation and reporting, recognise privacy risks and verify AI-generated work. Produce a team AI working agreement. PRACTITIONER — AI-Assisted Team Delivery & Coaching (in development). Design assisted workflows, improve backlog conversations and retrospectives, coach responsible use and measure effects on flow and quality. Produce a workflow and adoption experiment. ADVANCED — AI Delivery at Scale (in development). Coordinate dependencies, integrate evaluation and governance into delivery, improve planning and release readiness, and manage adoption across teams. Produce a programme delivery playbook and dashboard.

For Scrum Masters, Delivery Managers and Release Train Engineers (RTEs). Role-specific practice covers facilitation, delivery flow and cross-team planning. Outcome: improve delivery with evidence that AI helps performance while maintaining quality.

FOUNDATIONS — AI-Assisted Software Engineering (in development). Apply coding assistants to implementation, testing and documentation, review generated code and protect sensitive code and data. Produce a reviewed code change with automated tests. PRACTITIONER — Building AI Applications & Agents. Implement retrieval and tool use, define permissions and human approvals, evaluate behaviour and handle failures and untrusted inputs. Produce a working AI application or bounded agent. Related course: Agentic AI for Engineering Teams. ADVANCED — Production AI Architecture & Operations (in development). Design deployment pipelines, monitor quality, security, cost and latency, and implement rollback and incident response. Produce a production architecture and operational runbook.

For Software Engineers, DevOps Engineers and Architects. Advanced practice branches into implementation, operations and architecture. Outcome: deliver AI systems with tested behaviour, controlled access and operational visibility.