Introduction
As institutions expand their AI capabilities, it's essential to design a strategy that balances innovation and security. The process begins with tools like Microsoft Purview, Microsoft Entra, Defender, Intune, and Security Copilot to secure sensitive data and AI applications.
This module guides educational institutions in implementing AI data security using Microsoft Security tools to enhance data loss protection (DLP), a security solution that identifies and helps prevent unsafe or inappropriate sharing, transfer, or use of sensitive data. It provides hands-on practice for data security topics including:
- Identifying and categorizing sensitive data.
- Applying and managing sensitivity labels.
- Implementing DLP policies.
- Enhancing data protection and IT admin productivity with Security Copilot in Purview.
By the end of this module, participants are equipped with the knowledge and tools needed to better safeguard their institution's data.
Learning objectives
Upon completion of this module, you'll be able to:
- Describe about the dynamic nature of AI models and the key security challenges.
- Gain hands-on practice in the Microsoft Purview portal.
- Explore how Security Copilot integrates with Microsoft Purview to enhance incident analysis, manage hidden risks, streamline controls, and accelerate eDiscovery.