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Master Certificate Level 6-7 Leadership ISO IT & Related Technologies Artificial Intelligence

ISO 27091 — Privacy in AI Systems

ISO Certification Programme

6 Subjects
30 Chapters
156 Lessons
500 Marks

LAPT — London Academy of Professional Training

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ISO 27091 — Privacy in AI Systems
Master Certificate Level 6-7
  • IIT-AII-27091
  • Leadership Stage
  • 500 total marks
  • Pass: 325 marks (65%)
  • Validity: Lifetime
Enrol Now View Brochure
AwardMaster Certificate
Global LevelLevel 6-7
Total Marks500
Pass Mark325 (65%)
Subjects6
Chapters30
Classes156

About This Certification

Who Is This For?

This certification is intended for professionals in leadership roles such as Chief Information Officers, Data Protection Officers, and AI Project Managers who possess significant experience in information security and are looking to enhance their expertise in managing privacy within AI systems.

Course Curriculum

6 subjects • 30 chapters • 156 classes
01
Leadership in AI Privacy
5 chapters • 6 classes • 100 marks • 25h
Understanding Privacy Principles in AI Systems 6 classes
1.1 Define Key Privacy Principles in AI Context
1.2 Identify Legal and Ethical Frameworks Impacting AI Privacy
1.3 Analyze Case Studies of Privacy Failures in AI Systems
1.4 Assess the Role of Data Minimization in AI Privacy
1.5 Develop Strategies for Enhancing Transparency in AI Systems
1.6 Create an Action Plan for Implementing Privacy Principles in AI
Risk Assessment Framework for AI Privacy
Governance Structures for AI Privacy Management
Implementing Privacy by Design in AI Development
Leading Ethical AI Practices and Compliance
02
Audit and Compliance Processes
5 chapters • 30 classes • 75 marks • 25h
Understanding ISO 27091 and Its Importance in AI Privacy 6 classes
1.1 Define ISO 27091 and Its Relevance to AI Privacy
1.2 Identify Key Principles of ISO 27091 in AI Systems
1.3 Explain the Role of Leadership in Implementing ISO 27091
1.4 Analyze Common Compliance Challenges with ISO 27091 in AI
1.5 Evaluate Case Studies: Successful ISO 27091 Implementation in AI
1.6 Develop an Action Plan for ISO 27091 Compliance in Your Organization
Key Audit Principles and Frameworks for AI Systems 6 classes
2.1 Identify Key Audit Principles of AI Systems
2.2 Analyze ISO 27091 Compliance Requirements
2.3 Explore Frameworks for Auditing AI Systems
2.4 Develop Audit Objectives for AI Implementations
2.5 Assess Risks and Controls in AI Audit Processes
2.6 Implement Effective Audit Strategies for AI Privacy
Risk Assessment Methodologies for AI Privacy Compliance 6 classes
3.1 Identify Key Risks in AI Privacy Management
3.2 Analyze Existing Compliance Frameworks for AI Systems
3.3 Evaluate Risk Assessment Tools for AI Privacy
3.4 Develop a Privacy Risk Assessment Matrix for AI Projects
3.5 Formulate Risk Mitigation Strategies for Identified AI Privacy Risks
3.6 Implement a Continuous Monitoring Plan for AI Privacy Compliance
Conducting Compliance Audits in AI Environments 6 classes
4.1 Identify Key Compliance Requirements for AI Systems
4.2 Develop an Audit Framework Tailored for AI Environments
4.3 Plan and Schedule AI Compliance Audits Effectively
4.4 Implement Data Privacy Measures During Audits
4.5 Analyze Audit Findings in the Context of AI Data Usage
4.6 Create Actionable Recommendations to Enhance Compliance
Reporting and Continuous Improvement in AI Privacy Audits 6 classes
5.1 Analyze Current Reporting Standards for AI Privacy Audits
5.2 Identify Key Metrics for Continuous Improvement in AI Privacy
5.3 Develop Effective Reporting Templates for AI Privacy Findings
5.4 Implement a Feedback Loop for AI Privacy Audit Findings
5.5 Create an Action Plan for Addressing Compliance Gaps
5.6 Evaluate the Impact of Improvements on AI Privacy Management
03
Strategic Stakeholder Engagement
5 chapters • 30 classes • 75 marks • 20h
Understanding Stakeholder Dynamics in AI Privacy 6 classes
1.1 Identify Key Stakeholders in AI Privacy
1.2 Analyze Stakeholder Needs and Concerns
1.3 Map Stakeholder Influence on AI Privacy Dynamics
1.4 Develop Communication Strategies for Stakeholder Engagement
1.5 Facilitate Stakeholder Workshops on AI Privacy Issues
1.6 Evaluate Stakeholder Feedback to Enhance AI Privacy Policies
Mapping Stakeholder Influence and Interest 6 classes
2.1 Identify Key Stakeholders in AI Privacy
2.2 Analyze Stakeholder Influence on AI Privacy Decisions
2.3 Assess Stakeholder Interest Levels in AI Privacy Policies
2.4 Develop a Stakeholder Influence Matrix for AI Systems
2.5 Prioritize Stakeholders Based on Influence and Interest
2.6 Create a Strategic Engagement Plan for Key Stakeholders
Developing Stakeholder Engagement Strategies 6 classes
3.1 Identify Key Stakeholders for AI Privacy
3.2 Analyze Stakeholder Interests and Concerns
3.3 Develop a Stakeholder Engagement Matrix
3.4 Create Effective Communication Strategies for Stakeholders
3.5 Implement Feedback Mechanisms for Stakeholder Input
3.6 Evaluate and Adjust Engagement Strategies Based on Feedback
Communicating Privacy Measures to Stakeholders 6 classes
4.1 Identify Key Stakeholders for Privacy Communication
4.2 Analyze Stakeholder Concerns Regarding AI Privacy
4.3 Develop Clear Messages on Privacy Measures in AI
4.4 Utilize Effective Communication Channels for Stakeholder Engagement
4.5 Address Stakeholder Feedback on Privacy Initiatives
4.6 Evaluate the Impact of Communication Strategies on Stakeholder Trust
Evaluating and Adapting Stakeholder Engagement Approaches 6 classes
5.1 Identify Key Stakeholder Characteristics and Needs
5.2 Assess Current Stakeholder Engagement Strategies
5.3 Analyze the Impact of AI on Stakeholder Engagement
5.4 Develop Adaptive Stakeholder Engagement Frameworks
5.5 Implement Feedback Mechanisms for Stakeholder Involvement
5.6 Evaluate and Refine Engagement Approaches Based on Outcomes
04
Legal Frameworks for AI
5 chapters • 30 classes • 75 marks • 25h
Understanding AI and Privacy: Key Concepts and Definitions 6 classes
1.1 Define Key AI Privacy Terms
1.2 Explore the Concept of Data Minimization
1.3 Identify Privacy Risks in AI Systems
1.4 Analyze Legal Frameworks Governing AI and Privacy
1.5 Evaluate the Role of Consent in AI Privacy
1.6 Apply Privacy-by-Design Principles in AI Development
Regulatory Landscape: Global and UK-Specific Legal Frameworks for AI 6 classes
2.1 Explore the Evolution of AI Regulations Globally
2.2 Analyze Key UK Legislation Impacting AI Development
2.3 Identify Core Principles of Data Protection in AI Systems
2.4 Evaluate Compliance Challenges in AI Regulation
2.5 Compare International AI Regulatory Approaches
2.6 Propose Best Practices for Navigating the AI Regulatory Landscape
Risk Management in AI: Identifying and Mitigating Privacy Risks 6 classes
3.1 Understand Key Privacy Risks in AI Systems
3.2 Analyze Legal Frameworks Impacting AI Privacy
3.3 Identify Stakeholder Responsibilities in Privacy Risk Management
3.4 Assess Current Risk Management Practices in AI
3.5 Develop Strategies for Mitigating Privacy Risks
3.6 Implement a Risk Management Plan for AI Privacy
Ethics and Accountability in AI: Legal Obligations and Best Practices 6 classes
4.1 Define Key Ethical Principles in AI Systems
4.2 Explore Legal Obligations for AI Developers
4.3 Identify Best Practices for Accountability in AI
4.4 Analyze Real-world Case Studies of AI Ethical Dilemmas
4.5 Evaluate Impact of Non-compliance with AI Regulations
4.6 Develop an Accountability Framework for AI Implementation
The Future of AI Legislation: Emerging Trends and Challenges 6 classes
5.1 Analyze Global Trends in AI Legislation
5.2 Examine Key Privacy Standards Impacting AI Development
5.3 Identify Emerging Regulatory Challenges in AI Implementation
5.4 Discuss the Role of Stakeholders in Shaping AI Policies
5.5 Evaluate Case Studies of AI Legislative Responses
5.6 Propose Strategic Approaches to Comply with Future AI Laws
05
ISO 27091 Compliance
5 chapters • 30 classes • 100 marks • 35h
Understanding ISO 27091: Framework and Principles 6 classes
1.1 Define ISO 27091 and Its Importance in AI Privacy
1.2 Explore Key Principles of ISO 27091 Compliance
1.3 Identify Stakeholders in ISO 27091 Implementation
1.4 Analyze the Framework of ISO 27091 Compliance
1.5 Assess Risks and Challenges in Implementing ISO 27091
1.6 Develop a Plan for Achieving ISO 27091 Compliance
Identifying Privacy Risks in AI Implementations 6 classes
2.1 Define Privacy Risks in AI Systems
2.2 Identify Key Stakeholders in AI Privacy
2.3 Assess AI Data Handling Practices
2.4 Evaluate Legal and Regulatory Requirements
2.5 Analyze Potential Impact of Privacy Risks
2.6 Develop Mitigation Strategies for Privacy Risks
Establishing Compliance and Governance Structures 6 classes
3.1 Assess Current Governance Structures for Privacy Compliance
3.2 Identify Key Stakeholders in ISO 27091 Implementation
3.3 Develop a Privacy Governance Policy Framework
3.4 Define Roles and Responsibilities for Compliance
3.5 Establish Monitoring and Reporting Mechanisms
3.6 Create an Action Plan for Continuous Improvement in Governance
Developing Privacy Policies and Procedures for AI 6 classes
4.1 Identify Key Components of Privacy Policies for AI Systems
4.2 Analyze Regulatory Requirements for AI Privacy Compliance
4.3 Develop Risk Assessment Procedures for AI Privacy
4.4 Create Draft Privacy Policies Tailored for AI Applications
4.5 Review and Revise Draft Policies Based on Stakeholder Feedback
4.6 Implement Procedures for Ongoing Privacy Policy Evaluation
Auditing and Continuous Improvement in Compliance 6 classes
5.1 Identify Key Stakeholders for Auditing ISO 27091 Compliance
5.2 Establish Audit Objectives and Scope for AI Systems
5.3 Develop an Audit Plan and Timeline for Continuous Improvement
5.4 Implement Effective Data Collection Techniques for Auditing
5.5 Analyze Findings and Measure Compliance Against ISO 27091 Standards
5.6 Create a Continuous Improvement Framework Post-Audit
06
Privacy Risks in AI
5 chapters • 30 classes • 75 marks • 30h
Understanding Privacy Fundamentals in AI Systems 6 classes
1.1 Define Privacy and Its Importance in AI Systems
1.2 Identify Key Privacy Risks Associated with AI Technologies
1.3 Explore Regulatory Frameworks Impacting AI Privacy
1.4 Analyze Real-World Case Studies of Privacy Breaches in AI
1.5 Assess Strategies for Mitigating Privacy Risks in AI Systems
1.6 Implement Best Practices for Privacy Governance in AI Development
Identifying Privacy Risks in AI Development 6 classes
2.1 Define Key Privacy Concepts in AI
2.2 Identify Common Privacy Risks in AI Development
2.3 Analyze Real-World Examples of Privacy Failures in AI
2.4 Assess Privacy Risks Using Risk Assessment Frameworks
2.5 Recommend Best Practices for Mitigating Privacy Risks in AI
2.6 Develop a Privacy Risk Management Plan for AI Projects
Assessing Impact of AI Algorithms on Privacy 6 classes
3.1 Identify Key Privacy Concerns in AI Algorithms
3.2 Analyze Data Collection Methods of AI Systems
3.3 Evaluate the Impact of Bias in AI on Privacy
3.4 Assess Legal and Ethical Implications of AI Privacy
3.5 Develop Strategies for Mitigating Privacy Risks in AI
3.6 Create a Privacy Impact Assessment Framework for AI Projects
Mitigating Privacy Risks in AI Deployment 6 classes
4.1 Identify Key Privacy Risks in AI Systems
4.2 Assess Impact of Privacy Risks on Stakeholders
4.3 Explore Legal and Ethical Frameworks for Privacy in AI
4.4 Develop Mitigation Strategies for Privacy Risks
4.5 Implement Best Practices for Data Protection in AI
4.6 Evaluate the Effectiveness of Privacy Risk Mitigation Measures
Establishing Governance and Compliance for AI Privacy 6 classes
5.1 Identify Key Privacy Regulations Affecting AI Governance
5.2 Assess Privacy Risks Associated with AI Deployment
5.3 Develop a Framework for AI Privacy Compliance
5.4 Implement Data Protection Impact Assessments for AI Systems
5.5 Establish Roles and Responsibilities for AI Privacy Governance
5.6 Evaluate and Enhance AI Privacy Practices Through Continuous Monitoring

Assessment & Grading

Assessment Methods
  • Written Examination
  • Practical Assignment
  • Portfolio Assessment
Theory
50%
Practical
35%
Project
15%
ISO 27091 — Privacy in AI Systems
Master Certificate Level 6-7
Enrol Now View Brochure
Enrol Now

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