This foundational module introduces learners to modern healthcare data management using cloud-based platforms and industry standards. Students gain hands-on experience with Azure Health Data Services, learning to implement FHIR and HL7 standards for healthcare data normalization and interoperability. The module covers scalable storage architectures, real-time data processing systems, and integration with IoT medical devices. Learners explore data models, storage patterns, and API management while building practical skills in configuring compliant patient data storage solutions. Through comprehensive activities and practice assignments, students develop expertise in creating healthcare data infrastructures that support both operational workflows and analytical needs while maintaining regulatory compliance.

This critical security-focused module equips learners with advanced knowledge of healthcare cybersecurity and access management systems. Students learn to design and implement comprehensive identity and access management solutions using Microsoft Entra ID, including multi-factor authentication, conditional access policies, and role-based access control (RBAC). The module covers data encryption protocols, key management strategies using Azure Key Vault, and multi-layered security architectures that protect healthcare data at rest and in transit. Learners gain practical experience with break-glass procedures, privileged access management, and clinical context-aware access controls. Through hands-on activities, students master the balance between robust security measures and clinical workflow efficiency while ensuring compliance with healthcare regulations.

This advanced module explores cutting-edge privacy-preserving technologies and patient-centered security design in healthcare environments. Students learn to deploy Azure Confidential Computing for secure AI applications, implement trusted execution environments, and design multi-party computation scenarios for collaborative research. The module covers comprehensive de-identification techniques including Safe Harbor rules, Expert Determination, and synthetic data generation using automated tools. Learners develop expertise in privacy by design principles, creating patient-facing AI applications that maintain strict privacy controls while delivering valuable healthcare services. Through practical implementation activities, students master the integration of confidential computing, automated de-identification pipelines, and patient-centered design methodologies that enable innovation while protecting sensitive health information.

This comprehensive governance module provides learners with expert-level knowledge of healthcare data regulations and enterprise governance frameworks. Students explore global healthcare privacy laws including HIPAA, GDPR, and emerging regulations, learning to create multi-jurisdictional compliance strategies and technical control implementations. The module covers advanced auditing and monitoring using Microsoft Purview, including automated data classification, sensitivity labeling, and anomaly detection for suspicious access patterns. Learners develop skills in building comprehensive data governance programs, consent management frameworks, and data lifecycle policies that balance privacy protection with healthcare innovation. Through extensive practical exercises, students master the creation of compliance reporting systems, audit investigation workflows, and executive dashboards that demonstrate regulatory adherence while enabling strategic data initiatives.