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Responsible AI — Ethics, Risk & Governance

Beginner to Intermediate4-5 hoursAI risk map + personal responsibility checklist + governance starter framework

Using AI responsibly — covering ethics, bias, hallucination risk, data privacy, accountability, and organisational governance. The judgment to use AI fairly, safely, and in a way you can defend.

...questions to ask every time Bias — where fairness breaks down Risk — a framework for proportionate response Privacy and data — the lines you must not cross Transparency — can you defend it? Accountability — who...

1 DayIntensive

Beginner FriendlyNo legal background required

Responsible AI AI Ethics AI Risk AI Governance Bias Data Privacy AI Fluency View Details

Data and AI

Intermediate4-6 hoursData readiness assessment + governance framework + pipeline blueprint

The data foundations that make AI work. Data quality, governance, architecture, pipelines, and the GenAI shift from training to retrieval. Most AI failures are data failures — learn the patterns and prevent them.

Quick Navigation The data problem AI exposes Data quality — the six dimensions Data governance — who owns and protects it Data...

1.5 DaysIntensive

Data ReadinessAssessment

Data Quality Data Governance Data Architecture Feature Engineering Data Pipelines RAG Vector Databases GenAI Data AI Fluency View Details

Data & AI Direction

Intermediate to Advanced (SA, EA, TS)5-6 hoursData and AI direction framework + AI readiness assessment + governance overlay

How data strategy and AI direction connect to architecture — covering data quality, governance, data architecture for AI, AI enablement, responsible AI, data products, data mesh, and building a data and AI roadmap.

Quick Navigation Start here — Why data strategy is an architecture concern Data quality and governance Data architecture for AI AI enablement Responsible...

1.5 DaysIntensive

CurrentSA · EA · TS

Architecture Data Strategy AI Data Governance Data Mesh Data Products View Details

Complete Enterprise Data Architecture Framework: Business, Logical, Physical Layers with Real Templates

Most enterprises build data architectures one layer at a time. Business, logical, and physical layers exist as separate artefacts owned by separate teams. That separation is the structural gap that makes data estates ungovernable.

Executive Summary Who this is for: CTOs, Enterprise Architects, Data Architects, Chief Data Officers designing or operating enterprise data estates Problem it solves:...

Enterprise Architecture Data Architecture Technology Strategy Governance Data Governance Read Insight

Risk, Compliance & Control Points

Intermediate to Advanced (SA, EA, TS)5-6 hoursRisk and control register template + compliance mapping guide + architecture risk heat map

How architecture manages technical risk and meets regulatory obligations — covering architectural risk analysis, compliance by design, privacy by design, security controls as decisions, operational risk, control points, and demonstrating compliance through architecture.

Quick Navigation Start here — What architectural risk is Regulatory landscape Privacy by design Security controls as decisions Operational risk Control points Demonstrating compliance Putting...

1 DayIntensive

CriticalSA · EA · TS

Architecture Risk Compliance Security Governance Control Points View Details

AI Implementation & Technical Architecture

Intermediate to Advanced5-7 hoursAI architecture blueprint + MLOps framework + deployment playbook

Turning AI prototypes into reliable, scalable production systems. MLOps, model serving, RAG architecture, monitoring, and the engineering discipline that most AI projects are missing.

...operational backbone Model serving — making models accessible RAG architecture — grounding AI in your data Infrastructure design Monitoring — watching for silent degradation Scaling The production pipeline...

2 DaysIntensive

ArchitectureBlueprint

AI Architecture MLOps Model Deployment AI Infrastructure Production AI View Details

AI Procurement, Vendor Evaluation & Tool Selection

Beginner to Intermediate3-4 hoursVendor evaluation scorecard + tool selection checklist + risk review template

Choosing AI tools is not a beauty contest. Learn how to evaluate vendors, compare capabilities, assess risk, avoid lock-in, and buy systems that your organisation can actually govern and adopt.

...optimise for what is easiest to show. You need to evaluate what is easiest to hide. That includes: privacy and data handling access controls and logging configuration flexibility integration requirements cost...

Half DayDecision Focused

Vendor SelectionPractical

AI Procurement Vendor Evaluation Tool Selection Platform Strategy AI Governance View Details

Future of AI

Intermediate to Senior Leaders3-4 hoursAI horizon scan + strategic implications analysis + preparation roadmap

What's coming in AI — multimodal models, on-device AI, open-source momentum, protocols, regulation, and the shift to AI-native organisations. See around the corner without falling for hype.

...Multimodal AI expands what agents can do — agents can now see and hear, not just read. It creates new data challenges — images and audio need different pipelines than text. And it expands use cases dramatically:...

Half DayIntensive

Horizon ScanDeliverable

Future of AI AI Trends Multimodal AI AI Regulation Emerging Technology View Details

AI Agents and Automation

Intermediate to Advanced6-8 hoursAgent use case map + architecture blueprint + governance framework

AI agents — what they are, how they work, the protocols shaping them (MCP, A2A), and the governance you need before you let one act on your behalf. The bridge between AI that talks and AI that does.

...Observe Gathers information from tools, context, and memory Reads a file, searches the web, checks a database Orient Assesses current state and progress toward goal "I have 3 of the 5 data points I need"...

2 DaysIntensive

Agent DesignWorkshop

AI Agents Agentic AI MCP A2A Multi Agent Systems AI Orchestration View Details

How to Think With AI

Beginner to Advanced5-7 hoursPersonal AI Fluency framework + working habits

AI Fluency — the four competencies that separate people who use AI from people who think with it. Delegation, Description, Discernment, Diligence. Master these and everything else follows.

...What are the known limitations of this specific AI system? Are there biases baked into the training data that could surface in the output? Am I using it in a way it was designed for, or am I trying to...

2 DaysIntensive

4 CompetenciesComplete Framework

AI Fluency Generative AI Productivity AI Workflows Responsible AI View Details