Free course12 modules

AI Data Privacy & PII Management

Adopt AI without exposing sensitive data

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Built for CISOs, DPOs, compliance officers, engineering leads, product leaders handling sensitive data

Practical AI training for CISOs, DPOs, compliance officers, engineering leads, product leaders handling sensitive data

A practical guide for CISOs, DPOs, and engineering leads who want to unblock enterprise AI adoption while maintaining data privacy. Covers PII detection, redaction, the gateway pattern, compliance frameworks, and organisational training.

This course is designed for professionals who need to move from AI curiosity to useful implementation. The lessons focus on the workflows, risks, data requirements, governance questions, and ROI arguments that teams need before putting AI into production.

Each module is written as a working guide rather than a theory note. You can read it end to end, share individual lessons with colleagues, or use the module sequence as the outline for an internal workshop.

What you'll learn

The privacy problem — what actually happens when employees paste data into AI tools
PII detection — regex, NER, and LLM-based detection with Microsoft Presidio
The gateway pattern — sanitise data before it reaches cloud AI, re-hydrate on return
Regulatory compliance — GDPR, HIPAA, CCPA, EU AI Act, ITAR mapped to AI architectures
Vendor risk assessment — comparing OpenAI, Anthropic, Google, Microsoft data policies
Organisational training — AI acceptable use policies and the shadow AI problem

Outcomes

Explain where AI can help CISOs, DPOs, compliance officers, engineering leads, product leaders handling sensitive data without overstating what the technology can do.
Identify the data, privacy, workflow, and governance constraints that determine whether an AI use case is ready for production.
Build a clear business case using operational metrics, implementation costs, and measurable outcomes.
Create a practical next-step plan that connects the course material to a pilot, internal training session, or stakeholder discussion.

12 modules

1The Privacy Problem2Data Classification3Regulatory Landscape4PII Detection5Redaction & Anonymisation6The Gateway Pattern7Local Inference as Privacy8Building a Privacy Pipeline9Audit & Compliance10Vendor Risk Assessment11Training Your Organisation12Capstone Blueprint
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We'll audit your current AI data flows, design a detection and redaction pipeline, and map it to your regulatory requirements — so you can adopt AI without exposing sensitive data.

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