Course Description:
This course provides comprehensive coverage of security practices, governance, and scalability in AI systems. Learners will develop skills in protecting data, ensuring regulatory compliance, managing risks, and optimizing performance for enterprise-grade deployments.

Lecture 1: Enterprise Security Models
Understand core security mechanisms including authentication, encryption, access control, and auditing. Learn to implement vulnerability scanning and risk management frameworks for AI agents.

Key Objectives:

• Agent authentication and authorization
• Data encryption & privacy protection
• Access control systems
• Audit trails and compliance reporting
• Vulnerability scanning and protection
• Risk management frameworks

Lecture 2: Governance Frameworks
Explore AI governance through ethics, bias mitigation, and adherence to regulations like GDPR and HIPAA. Develop strategies to embed responsible AI principles.

Key Objectives:

• AI ethics implementation
• Bias detection and mitigation
• Regulatory compliance (GDPR, HIPAA, etc.)

Lecture 3: Scalability & Performance
Learn to scale AI systems horizontally with load balancing, caching, and resource management techniques. Optimize performance while maintaining security and compliance.

Key Objectives:

• Horizontal scaling strategies
• Load balancing across agent instances
• Caching and optimization techniques
• Resource allocation and management