AI Champion (AIC) - Bundles 4, 5 & 6

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Data protection and legislation in the context of AI (AIC4C1)

In this course, you’ll explore the types of system updates an AI Support champion manages, how AI is changing the update picture, the risks of unpatched systems and how to follow a secure update process in line with organisational policy.

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System updates, maintenance and security (AIC4C2)

In this course, you’ll explore the importance of maintaining and securing systems as part of your role as an AI Support champion.

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Backup and business continuity (AIC4C3)

In this course, you'll explore why backup matters and how restore points and rollback work, compare backup methods, learn what business continuity and disaster recovery planning mean for your role and recognise the impact of data loss.

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AI problem-solving lifecycle and diagnostic tools (AIC5C1)

In this course, you'll move from understanding systems to applying a structured approach. You'll learn how to diagnose digital problems, identify AI support tool issue types, respond to enquiries and follow a reliable issue resolution process.

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CRAAP (AIC5C2)

In this course, you'll learn how to judge whether the information you find while diagnosing a problem is reliable enough to act on, what can go wrong when it isn't and how to search for help online without creating security or data-sharing risk.

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Prompt engineering (AIC5C3)

In this course, you will learn how to write, refine and evaluate prompts so AI tools produce more useful outputs for everyday support work, team documentation and continuous improvement.

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Data lifecycles - create, process, analyse, store, destroy (AIC6C1)

In this course, you'll learn to identify the five stages of the data lifecycle, understand how data moves through each stage and recognise how your decisions influence data quality, system outcomes and AI outputs through careful data handling.

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Types of data and data structures (incl. databases) (AIC6C2)

In this course, you'll learn the difference between data types, how databases are structured, how real systems organise information and how to recognise when a problem is caused by the structure of the data itself.

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Data quality and its impact on AI outputs (AIC6C3)

In this course, you'll explore what data quality means in practical terms, how different quality issues create different kinds of risk and why that matters when systems and AI support tools rely on data to retrieve, describe or summarise information.

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Using AI to summarise and process information (AIC6C4)

In this course, you'll focus on what happens when large amounts of information need to be turned into something usable at speed. You'll explore the difference between summarising and processing, how both support workplace decisions and efficiency.