This program builds foundational AI auditing skills. It covers planning, evidence, risk, and compliance. Learn through case studies. This certification equips professionals to navigate the complexities of AI system audits. Understand core audit principles, risk assessment, and compliance frameworks. Develop practical skills to evaluate AI systems effectively. Gain expertise in reporting and communication of audit findings.
Audience: Entry-to-mid-level professionals.
Learning Objectives:
- Understand AI audit planning.
- Identify AI-specific audit evidence.
- Apply AI risk and compliance frameworks.
- Analyze AI systems using case studies.
Program Modules:
- Module 1: Audit Planning:
- Defining audit scope.
- Risk assessment methods.
- Developing audit programs.
- Stakeholder engagement.
- Resource allocation.
- Documentation standards.
- Module 2: AI-Specific Audit Evidence:
- Data integrity checks.
- Algorithm validation.
- Bias detection techniques.
- Model performance analysis.
- System log review.
- Output verification.
- Module 3: AI Risk Frameworks:
- Identifying AI vulnerabilities.
- Evaluating risk impact.
- Risk mitigation strategies.
- Control implementation.
- Monitoring risk levels.
- Reporting risk findings.
- Module 4: AI Compliance Frameworks:
- Regulatory requirements.
- Ethical guidelines.
- Data privacy standards.
- Industry best practices.
- Legal considerations.
- Compliance documentation.
- Module 5: Case Analysis:
- Real-world audit scenarios.
- Problem-solving techniques.
- Decision-making processes.
- Audit report generation.
- Identifying control gaps.
- Best practice applications.
- Module 6: Audit Reporting:
- Report structure and format.
- Findings presentation.
- Recommendations development.
- Executive summaries.
- Follow-up actions.
- Communication skills.
Exam Domains:
- Framework Governance.
- Data Integrity Assessment.
- Algorithmic Validation.
- Risk Mitigation Strategies.
- Compliance Evaluation.
- Reporting and Communication.
Course Delivery:
The course is delivered through lectures and interactive discussions. Participants access online resources, including readings and case studies.
Assessment and Certification:
Participants are assessed through quizzes and assignments. Upon completion, participants receive a certificate.
Question Types:
- Multiple Choice Questions (MCQs)
- True/False Statements
- Scenario-based Questions
- Fill in the Blank Questions
- Matching Questions (Matching concepts or terms with definitions)
- Short Answer Questions
Passing Criteria:
To pass the Certified AI Auditor (CISA) (Tonex version) Certification Training exam, candidates must achieve a score of 70% or higher.
Enroll today and advance your AI auditing career.