Securing AI in Education with Security Copilot and Data Protection

As educational institutions rapidly adopt artificial intelligence, safeguarding sensitive student and staff data has never been more critical. School administrators and IT professionals must ensure that AI integration does not compromise privacy or violate compliance standards. This text-only course guides you through the foundational concepts and practical configurations needed to secure AI deployments in schools. You will learn how to establish robust data protection frameworks, prevent accidental data leaks, and leverage advanced security assistants to monitor your educational tenant. What you'll learn: - Understand foundational security concepts and zero-trust principles tailored for educational environments. - Configure data loss prevention policies to block sensitive student information from being shared with public AI models. - Apply sensitivity labels to classify and protect school records, grading data, and administrative files. - Utilize Security Copilot to analyze threats, investigate security alerts, and automate incident response. - Establish governance policies for safe generative AI adoption among students and educators. - Practice auditing and monitoring data access patterns to maintain continuous compliance with education privacy laws. This course starts with essential definitions and security frameworks before moving into step-by-step written guides for configuring security policies and labels. You will read through practical scenarios and analyze realistic configurations designed specifically for school environments. Designed for school IT administrators, educational technology coordinators, and data protection officers seeking to secure AI tools without any advanced prior security experience. Start reading today to build a safer, AI-ready learning environment for your school.