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Data Governance, Privacy & Integrity in Artificial Intelligence (AI)
Enhancing AI reliability through data governance, privacy, and ethical integrity.
course :
IT Management Training Courses
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
- 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
- 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
Upon successful completion of this training program, participants will be formally awarded a HighPoint Certificate, recognizing their demonstrated knowledge and competencies in the subject matter. This certificate serves as an official testament to their proficiency and commitment to professional development
Training Schedule and Fees
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