Program in AI Security, Privacy & Governance

Categories: Cybersecurity
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About Course

Use AI with confidence by managing its security, privacy and governance risks.

This program shows organizations how to adopt AI responsibly, from understanding its risks to protecting data, securing LLM applications and building governance that actually works. You study privacy principles under GDPR, US state laws and Brazil's LGPD, defensive controls for AI systems, bias and transparency practices, and frameworks such as the NIST AI RMF, ISO/IEC 42001 and the EU AI Act. Each course is self-paced, uses free tools and ends with a practical deliverable. You finish with a complete AI governance plan for an organization that you can keep in your portfolio.

44 hours · 7 courses, from Explore to Advance, ending with a final project · Certificate of completion · 12-month access

Who it is for

Managers, compliance and privacy professionals, IT and security staff, and small-business owners who are deploying or approving AI tools. No programming background is required for most courses.

Prerequisites

Familiarity with common workplace software and a general idea of what generative AI tools do is enough to start.

What you will be able to do

  • Identify and prioritize AI risks across security, privacy, fairness and operations
  • Apply privacy principles and data protection controls to AI use cases
  • Design defensive controls and human oversight for AI systems and LLM applications
  • Build AI policies, risk assessments and audit evidence aligned with recognized frameworks

Courses in this program

Buy the complete program for 10% less than the courses separately, or start with one course and continue at your own pace.

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What Will You Learn?

  • Identify and prioritize AI risks across security, privacy, fairness and operations
  • Apply privacy principles and data protection controls to AI use cases
  • Design defensive controls and human oversight for AI systems and LLM applications
  • Build AI policies, risk assessments and audit evidence aligned with recognized frameworks

Course Content

AIS101 · AI Risks: An Overview for Organizations (4 h)
Get a clear, practical map of the risks that come with using AI at work, from data leaks and wrong answers to bias, security threats and legal exposure, and learn how to start managing them.

  • Lesson 1 · How AI systems work and where they fail
  • Lesson 2 · A map of AI risks
  • Lesson 3 · Inventory, risk register and first controls
  • Lesson 4 · Lab and assignment
  • AIS101 Assessment · AI Risks: An Overview for Organizations

AIS102 · Data Privacy Principles (LGPD, GDPR and Beyond) (4 h)
Learn the core principles of modern data privacy law across the GDPR, US state privacy laws and Brazil's LGPD, and apply them to everyday business processes and AI use cases.

AIS103 · Securing AI Systems and LLM Applications (6 h)
Protect AI systems and LLM applications with a defense-in-depth approach. You threat-model an LLM app using the OWASP Top 10 for LLM Applications and MITRE ATLAS, apply layered controls and verify them with automated evaluations.

AIS104 · Responsible AI: Bias, Transparency and Human Oversight (6 h)
Put responsible AI into practice: detect and reduce bias, make AI use transparent to the people it affects, and design human oversight that actually works rather than rubber-stamping.

AIS105 · AI Governance Frameworks and Policies (8 h)
Build an AI governance structure that fits your organization using the NIST AI RMF, ISO/IEC 42001 and the EU AI Act, and turn it into clear policies, roles and approval workflows.

AIS106 · AI Risk Assessment and Audit in Practice (8 h)
Assess AI risks systematically and audit AI systems against policies and frameworks. You plan an audit, gather and test evidence, rate findings and write a report that leadership can act on.

AIS107 · Final Project: An AI Governance Plan for an Organization (8 h)
Bring the program together by building a complete, practical AI governance plan for an organization, covering inventory, risk, privacy, security, responsible AI, policies, oversight and audit.

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