Advanced in AI Risk (AAIR)

أدر مخاطر الذكاء الاصطناعي عبر دورة حياته. خلال يومين تدمج مخاطره في أطر الحوكمة

يومانمتقدّم3 وحدات

نظرة عامة

أدر مخاطر الذكاء الاصطناعي عبر دورة حياته. خلال يومين تدمج مخاطره في أطر الحوكمة، وتعالجها في مراحل التصميم ومتطلبات البيانات والتطوير والشراء، وتشغّل برنامجاً لإدارتها يشمل تقييم السيناريوهات ونمذجة التهديدات، استعداداً لشهادة AAIR.

المنهاج

المحتوى التقني أدناه معروضٌ باللغة الإنجليزية كما ورد في منهاج الدورة، حفاظاً على دقّة المصطلحات.

3 وحدات

AI Models, Frameworks, Strategies, and Use Cases
Types of AI
AI Frameworks
Business Use Case and AI Use Case Review
AI Business Strategies
AI Organizational Processes and Alignment
AI Governance Fundamentals
Alignment to Existing Organizational Structures
AI Ownership, Oversight, and Accountability
AI-related Roles and Responsibilities
Accountability and AI
RACI for AI Solutions
AI Policies, Procedures, and Organizational Training
AI Acceptable Use Policy
AI Policy Development
AI Procedures and Manuals
Organizational Culture and AI Risk Governance
Elements of Effective AI Training and Awareness
AI Regulatory Compliance and Legal Considerations
Compliance With Laws and Regulations
Gaps in Regulatory Coverage
Mapping Legal Requirements for AI
Assessing Legal Exposure and Liability for AI Actions
Intellectual Property Considerations in AI
Vendor Contract Review
AI Trustworthiness, Ethical and Societal Implications
Responsible Use of AI Systems 68
Bias and Fairness
Transparency and Explainability
Trust and Safety
Human Rights and Societal Impact
Environmental Impact

AI Design, Development, Procurement, and Documentation
Plan and Design
Data Requirements for AI Models
Procurement of AI Solutions
Build, Adapt, and Document Models
AI Model Training, Testing and Validation
Sourcing Datasets
Validating the Data
Model Training
Model Testing and Validation
Model Performance and Fine Tuning
AI Implementation, Maintenance, and Decommissioning
AI Deployment and Implementation
Robustness and Scalability Considerations
Monitoring and Managing Model Drift
Change Management in AI Systems
Decommissioning AI Solutions
AI Data and Asset Management
AI Asset Inventory
Data Collection for AI
Data Classification
Data Confidentiality
Data Quality
Data Balancing
Data Scarcity
Data Security
Data Preparation and Normalization
Data Minimization and Privacy Considerations

AI Risk Scenario Identification and Assessment
AI Threat Landscape
AI Threat Modeling
Development of AI Risk Scenarios
AI Risk Classification
AI Risk Assessment
AI Risk Treatment Strategies
Accept
Avoid
Mitigation
Transfer/Share
AI Controls Management
AI Control Types and Control Frameworks
AI Control Selection and Validation
Control Performance
Controls Specific to AI Solutions
Use of AI in Control Management
AI Risk Metrics, Monitoring, and Reporting
Risk and Performance Metrics
AI Risk Reportings
AI Supply Chain Risk Management
AI Vendor Management
AI Shared Responsibility Model
AI Software Supply Chain Risk
Cloud Computing Risk in AI Supply Chains
AI Incident Response, BIA, Business Continuity, and Disaster Recovery
AI Business Impact Analysis
Prepare
Identify and Report
Assess
Respond
Post-incident Review

لمن هذه الدورة

مختصو المخاطر الحاصلون على CRISC أو ما يماثلها.

قبل أن تبدأ

Requires existing certification (typically one of the following): CRISC (primary path) or similar: CISA, CISM, CGEIT, CDPSE - Designed for experienced risk professionals

3 أيام

تفاصيل الدورة ←

لنرسم خطوتك التالية معاً.

أخبرنا بالدورة أو الشهادة التي تهمّك، ونرسل لك المنهاج والمواعيد القادمة والرسوم وخيارات التدريب الخاص لفريقك.

تحدّث إلى مستشار ←واتساب