This course is designed to equip participants with the knowledge and skills required to protect sensitive information and manage data security risks in the era of AI.

Participants will learn how Microsoft Purview helps organisations discover, classify, protect, and govern sensitive data across Microsoft 365 and AI-enabled environments. The course covers key areas such as data security posture management for AI, sensitivity labels, data loss prevention, insider risk, information protection, compliance controls, and strategies to reduce oversharing and data leakage when using generative AI tools.

Through structured learning, practical examples, and scenario-based guidance, participants will gain the confidence to use Microsoft Purview to strengthen data protection, support compliance requirements, and enable safer AI adoption.

This course is suitable for professionals who want to understand the fundamentals of AI and machine learning and how these technologies are applied in business and technology environments.

Typical participants include:

• Business and technology professionals
• Data analysts and digital transformation teams
• IT professionals and software developers
• Project managers working on AI-related initiatives
• Professionals interested in emerging technologies and innovation

It is also beneficial for organisations exploring AI adoption and data-driven decision making.

Participants should have basic knowledge of Microsoft 365 services, security, compliance, and data protection concepts.

Before attending this course, participants are recommended to have:

• Basic understanding of Microsoft 365 services
• Familiarity with security and compliance concepts
• Basic knowledge of data loss prevention and sensitivity labels
• Awareness of generative AI tools such as Microsoft 365 Copilot
• General understanding of data governance and information protection

At the end of this course, participants will be able to:

• Understand AI-related data security risks and the role of Microsoft Purview
• Identify, classify, and protect sensitive information across Microsoft environments
• Apply sensitivity labels, data loss prevention, and information protection controls
• Use Microsoft Purview capabilities to reduce oversharing and data leakage risks
• Support safer AI adoption through data governance and compliance practices

• Introduction to Microsoft Purview and data protection in the AI era
• Understanding AI-related data security risks, oversharing, and sensitive data exposure
• Identifying and classifying sensitive information using Microsoft Purview
• Applying sensitivity labels, information protection, and data loss prevention policies
• Using Data Security Posture Management for AI to identify and mitigate risks
• Managing insider risk, audit, compliance, and governance capabilities
• Supporting responsible and secure AI adoption with Microsoft Purview