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Data Governance, Privacy & Integrity in Artificial Intelligence (AI)
course
IT Management and Cyber Security
Course Overview
This Data Governance, Privacy & Integrity in Artificial Intelligence (AI) training course has been developed to enhance delegates understanding of AI.
In today's data-driven world, the intersection of AI implementation and privacy protection presents both significant challenges and opportunities for organizations.
This intensive five-day training course equips senior leaders with comprehensive knowledge and practical tools to navigate the complex landscape of AI data governance and privacy compliance.
Drawing from real-world examples, participants will master the art of balancing innovation with privacy protection.
The training course incorporates current privacy regulations, including Saudi Arabia's PDPL and international frameworks, providing a thorough understanding of global and regional privacy requirements.
This training course will feature:
Comprehensive understanding of AI privacy regulations and frameworks
Practical tools for implementing privacy-compliant AI systems
Real-world case studies from leading organizations
Hands-on experience with privacy impact assessments
Strategic approaches to building privacy-oriented AI frameworks
Course Objectives
At the end of this training course, you will learn to:
Understand current AI regulatory landscapes across global regions
Master adaptive governance approaches for AI systems
Develop practical skills in AI risk assessment and compliance
Create adaptive governance frameworks for organizations
Apply real-world case studies to organizational challenges
Course Audience
This training course is suitable for a wide range of professionals who are involved in AI, governance, risk management, compliance, and decision-making processes within their organizations.
The training course content is designed to benefit participants from various industries, including oil and gas, financial services, manufacturing, and telecommunications, among others.
Course Methodology
This training course adopts a blended learning approach that integrates interactive lectures, group discussions, case studies, and practical exercises to ensure a well-rounded and engaging learning experience.
Participants will actively engage in analytical discussions, evaluate real-world scenarios, and translate theoretical concepts into practical applications relevant to their professional contexts.
The course facilitator will leverage extensive industry expertise to share best practices, provide insights, and offer tailored guidance to participants.
In addition, the program creates valuable opportunities for peer-to-peer networking, enabling participants to exchange experiences and collaboratively develop actionable strategies for enhancing corporate governance within their organizations.
Course Outline
DAY 1
Global Data Privacy Landscape and AI
Global Privacy Framework
EU GDPR and AI Systems
China's Personal Information Protection Law (PIPL)
Saudi Arabia's Personal Data Protection Law (PDPL)
UAE Federal Decree Law No. 45 of 2021
African Data Protection Harmonization Framework
Regional Focus
SAMA Data Privacy Guidelines
Qatar Financial Centre Privacy Rules
African Regional Frameworks
Privacy implementation in AI systems
Cross-border data transfer solutions
Compliance monitoring systems
DAY 2
AI Data Governance Frameworks
Core Components
Data Classification Systems
Data Lifecycle Management
Privacy by Design Principles
Data Quality Management
Implementation
Data Governance Operating Models
Privacy Impact Assessments
Data Protection Controls
Monitoring Systems
DAY 3
AI Privacy Risk Management
Risk Framework
Privacy Risk Assessment Models
Data Protection Impact Assessments
Vendor Risk Management
Cross-border Data Transfers
Technical Controls
Data Anonymization Techniques
Encryption Standards
Access Control Systems
Audit Mechanisms
Risk assessment methodology
Technical controls implementation
Compliance monitoring
DAY 4
Practical Implementation
Organizational Integration
Privacy Governance Structure
Role Definition and Responsibilities
Training and Awareness
Change Management
Monitoring
Privacy Metrics Development
Incident Response
Reporting Frameworks
Continuous Improvement
DAY 5
Future Trends
Emerging Topics
Privacy-Preserving AI Techniques
Federated Learning
Synthetic Data
Edge Computing Privacy
Certificates
On successful completion of this training course, HighPoint Certificate will be awarded to the delegates. Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.