Week 1: Privacy Fundamentals and Legal Frameworks

• Evolution of privacy concepts and historical context
• Key global privacy regulations:
  • General Data Protection Regulation (GDPR)
  • California Consumer Privacy Act (CCPA) and Privacy Rights Act (CPRA)
  • Health Insurance Portability and Accountability Act (HIPAA)
  • Other regional and sectoral regulations
• Core privacy principles:
  • Lawfulness, fairness, and transparency
  • Purpose limitation
  • Data minimization
  • Accuracy
  • Storage limitation
  • Integrity and confidentiality
  • Accountability
• Rights of data subjects
• Organizational responsibilities and obligations
• Jurisdictional considerations and regulatory scope
• Lab: Mapping regulatory requirements to organizational processes

Week 2: Privacy by Design and Data Governance

• Privacy by Design principles and implementation
• Data inventory and mapping methodologies
• Data classification frameworks
• Personal data identification techniques
• Data flow documentation
• Data minimization strategies and implementation
• Purpose limitation in practice
• Lawful bases for processing
• Consent management systems
• Privacy governance structures
• Role of Data Protection Officer (DPO)
• Implementing accountability measures
• Lab: Creating a data inventory and classification scheme

Week 3: Technical Privacy Controls

• Pseudonymization techniques:
  • Tokenization
  • Hashing
  • Key management
• Anonymization approaches:
  • K-anonymity
  • L-diversity
  • T-closeness
  • Differential privacy
• Encryption fundamentals:
  • Symmetric vs. asymmetric encryption
  • Transport encryption (TLS/SSL)
  • Storage encryption
  • End-to-end encryption
• Access controls and authentication:
  • Role-based access control (RBAC)
  • Attribute-based access control (ABAC)
  • Multi-factor authentication
• Database privacy controls:
  • Column-level encryption
  • Dynamic data masking
  • Row-level security
• Privacy in APIs and microservices
• Privacy-enhancing technologies (PETs)
• Lab: Implementing pseudonymization and access controls

Week 4: Privacy Impact Assessment and Risk Management

• Privacy risk assessment methodologies
• Conducting Data Protection Impact Assessments (DPIAs):
  • When DPIAs are required
  • DPIA process and documentation
  • Stakeholder consultation
  • Risk evaluation and mitigation
• Legitimate interest assessments
• Vendor privacy assessment:
  • Due diligence processes
  • Contractual requirements
  • Ongoing monitoring
• Risk mitigation strategies:
  • Technical controls
  • Organizational measures
  • Contractual safeguards
• Documentation and evidence collection
• Lab: Conducting a DPIA for a sample system

Week 5: Data Breach Prevention and Response

• Common causes of data breaches
• Technical safeguards against breaches:
  • Network security
  • Endpoint protection
  • Data loss prevention (DLP)
  • Security monitoring
• Building a data breach response plan:
  • Breach detection mechanisms
  • Initial assessment
  • Containment strategies
  • Investigation procedures
  • Remediation steps
• Notification requirements and timelines:
  • Regulatory authorities
  • Affected individuals
  • Third parties
• Documentation and evidence preservation
• Post-breach remediation
• Lessons learned and continuous improvement
• Lab: Data breach tabletop exercise

Week 6: Privacy Program Implementation and Case Studies

• Building a privacy program:
  • Program structure and governance
  • Policy development
  • Procedures and standards
  • Training and awareness
  • Monitoring and auditing
  • Continuous improvement
• Privacy awareness and training strategies
• Privacy considerations in emerging technologies:
  • Artificial intelligence and machine learning
  • Internet of Things (IoT)
  • Blockchain
  • Biometrics
• International data transfers:
  • Adequacy decisions
  • Standard contractual clauses
  • Binding corporate rules
  • Derogations
• Real-world case studies and lessons
• Future trends in privacy protection
• Capstone project: Designing a privacy program
• Course review and final assessment

Assessment Components

1. Weekly Assignments (40%)
   • Practical exercises
   • Case analyses
   • Technical implementations
   • Reading responses
2. Privacy Impact Assessment Project (20%)
   • Comprehensive DPIA for a sample system
   • Risk assessment and mitigation strategy
3. Data Breach Response Exercise (15%)
   • Simulation response
   • Documentation and analysis
4. Capstone Project (20%)
   • Privacy program design
   • Implementation roadmap
   • Presentation
5. Participation and Engagement (5%)
   • Contribution to discussions
   • Peer collaboration
   • Q&A participation

Grading Scale

• A: 90-100%
• B: 80-89%
• C: 70-79%
• D: 60-69%
• F: Below 60%

Attendance and Participation

• Instructor-led format: Attendance at live sessions is strongly encouraged
• Self-paced format: Regular progress through course materials is expected
• Active participation in discussions and exercises is essential for full understanding

Confidentiality

• Case discussions may involve sensitive topics
• Respect confidentiality of discussions and examples shared by instructors and peers
• Apply Chatham House Rules to discussions of real-world examples

Academic Integrity

• All work must be original or properly attributed
• Collaboration is encouraged, but individual assignments must reflect individual work
• Proper citation of sources is required for all research-based assignments