AI Awareness Training — Fast, Practical, Auditable
Short, self-paced micro courses for your teams. Build AI data readiness, compliance, and practical skills—on demand.
On-demand
Certificate of Completion
Explore Our AI Awareness Courses
Future Trends in AI Governance
Equip your team to anticipate where AI governance is heading—covering autonomous decision-making, cross-border coordination, emerging ethics around advanced systems, and the co-evolution of standards and technology. You’ll turn fast-moving regulatory and standards signals into practical guardrails for products, policies, and risk management so your organisation can innovate with confidence.
Ethical Deployment in Specific Sectors
A concise, sector-by-sector guide to deploying AI responsibly in healthcare, finance, the public sector, and education. You’ll learn how to spot ethical risks, reduce harm, and align AI initiatives with governance, safety, and compliance expectations—so teams can innovate without eroding trust.
Human Oversight and AI Control
A practical, risk-aware primer on keeping people meaningfully in control of AI systems. You’ll learn when to place humans in or on the loop, how to design effective overrides and failsafes, and how to assign accountability and monitoring so high-stakes decisions are safe, auditable, and compliant.
Ethics in Generative AI
Build practical literacy in the ethical use of generative AI, from detecting deepfakes to deploying responsible guardrails. This concise micro-course helps organisations reduce risk, protect brand trust, and align AI adoption with legal and societal expectations.
Responsible Data Governance
Equip your teams with practical, responsible data governance practices for AI initiatives. This micro-course shows how to trace where data comes from, respect user rights and consent, minimise sensitive information, and handle cross-border data risks so AI projects stay compliant, ethical, and resilient.
AI Auditing and Assurance
Equip your team with the essentials of AI auditing and assurance so you can evidence control over AI systems and reduce regulatory and reputational risk. Learn practical audit methodologies, how to scope internal and third-party reviews, and how to implement audit trails and logging that stand up to scrutiny—aligned to recognised certification schemes such as ISO/IEC 42001.
Corporate AI Governance Structures
A fast, practical primer on how enterprises govern AI—from setting up ethical oversight to embedding controls across the AI lifecycle. You’ll learn the structures, roles, and processes that keep AI initiatives compliant, auditable, and aligned with business risk appetite.
Bias, Discrimination, and Fairness
This bite-size course shows how AI systems can encode and amplify bias, what that means for discrimination and fairness, and how to respond responsibly. You’ll learn practical ways to surface and measure bias, weigh fairness trade-offs, and design redress mechanisms so decisions remain transparent and accountable.
Trustworthy AI Design
Equip your team with the essentials to design and deploy AI that people can trust—explainable, private, secure, and inclusive. This micro-course turns high-level principles into practical steps and checklists your staff can apply immediately across the AI lifecycle. The result: lower risk, stronger compliance, and AI outcomes that stakeholders can understand and support.
AI Risk Management
This micro-course equips teams to recognise, assess, and respond to AI risks across everyday workflows and products. You’ll learn a repeatable approach to risk identification and classification, run AI Risk Impact Assessments (AIRIA), and translate policy into practical guardrails and controls. The course ends with incident response and harm-mitigation techniques that satisfy stakeholders and align with emerging regulation.
Regulatory Landscape and Emerging Policies
A focused, non-technical briefing on the fast-evolving AI regulatory landscape and how it affects real-world deployments in organisations. You’ll get a clear, side-by-side view of major frameworks—including the EU’s approach, the US NIST AI Risk Management Framework, China’s governance directives, and soft-law/industry self-regulation—so you can reduce compliance risk, earn stakeholder trust, and move from uncertainty to action.
Ethical Frameworks for AI
A fast, practical primer on the core ethical frameworks that guide responsible AI in the workplace. You’ll learn how utilitarian, rights-based, and justice-oriented approaches shape real decisions, and how to apply them to everyday AI features, policies, and reviews—especially where autonomy and human oversight intersect.
Introduction to AI Governance
This micro-course demystifies AI governance and gives busy teams a common language and a practical starting point to use AI responsibly. You’ll explore the core principles—transparency, accountability, and fairness—how they apply in day-to-day decisions, and how global versus local requirements shape your approach.
Market Intelligence and Agribusiness Innovation
A fast, practical primer on how AI unlocks market intelligence and innovation in the agribusiness value chain. You’ll see how modern tools forecast commodity prices, assess product–market fit, surface startup trends and valuations, and enable new fintech/insurtech models—so teams can make quicker, lower-risk, data-driven decisions.
Food Security and Policy Forecasting
This micro-course shows how AI can forecast food security risks, simulate policy options, and guide timely aid decisions. You’ll learn where these models add value, their limits and ethical considerations, and how to turn outputs into practical actions for governments, NGOs, and supply chains.
AI in Food Production and Processing
A fast, practical introduction to how modern AI improves food production and processing—from predicting equipment failures and optimizing formulations to automating packaging and evaluating taste and texture. Learn where AI delivers measurable value, how to start small, and how to scale safely to reduce waste, boost yield, and enhance product consistency.
Sustainable and Regenerative Agriculture
Learn how modern AI supports regenerative and sustainable farming—from optimizing crop rotations and cover crops to monitoring biodiversity and soil health. This micro-course shows how predictive models and precision approaches can cut inputs, boost resilience, and unlock credible carbon outcomes that matter for ESG reporting and supply-chain commitments.
AI for Food Safety and Quality Control
This micro-course shows how artificial intelligence can strengthen food safety and quality control across the production line—from camera-based grading and sorting to predictive microbiology, traceability, and spoilage detection. You’ll learn where AI adds measurable value, what data and governance are required, and how to pilot solutions that align with existing compliance frameworks.
AI in Agricultural Supply Chain Optimisation
This micro-course shows how AI can streamline agricultural supply chains end-to-end—from demand and supply forecasting to routing, cold-chain monitoring, and real-time visibility. You’ll learn practical approaches to cut post-harvest losses, reduce logistics costs, and improve service levels using accessible tools and proven patterns.
Farm Data Platforms and Decision Support
Give your team a fast, practical tour of how modern farm data platforms turn raw sensor, machinery, and satellite feeds into confident, timely decisions. You’ll see how integrated data lakes and knowledge graphs create a unified view, how predictive and prescriptive analytics drive planning and resource allocation, and how mobile/edge AI brings insights to the field when and where they’re needed.