Home » Courses » Certification Courses » AI Certificates » AI Cybersecurity & Trust » Certified Trustworthy AI Professional (C-TAIP)

Certified Trustworthy AI Professional (C-TAIP)

Length: 2 Days
Print Friendly, PDF & Email

Certified Trustworthy AI Professional (C-TAIP) Certification Program by Tonex

Certified MBSE + AI Professional (C-MBSE+AI-P)

Trustworthy AI is now a business requirement. This program builds practical capability in bias, fairness, robustness, and transparency. You learn how to design, evaluate, and operate AI systems that people can trust. We align methods and governance with the NIST AI Risk Management Framework and ISO/IEC 42001. You practice clear documentation and measurable assurance. You connect data decisions to ethical outcomes. You translate standards into day-to-day workflows.

Cybersecurity impact is central. Robust models resist adversarial manipulation. Secure pipelines reduce attack surface. Monitoring detects drift, misuse, and anomalous behavior. Governance keeps evidence ready for audits and incidents. You finish with a toolkit for risk-aware delivery. You can brief executives and satisfy compliance. You can ship safer features faster. The result is resilient, explainable AI that earns user confidence.

Learning Objectives:

  • Identify and mitigate bias across the AI lifecycle.
  • Apply fairness metrics and evaluate trade-offs.
  • Strengthen robustness against attacks and failures.
  • Produce actionable transparency and explanations.
  • Operationalize NIST AI RMF and ISO/IEC 42001 controls.
  • Build monitoring, incident response, and audit evidence.

Audience:

  • Cybersecurity Professionals
  • AI/ML Engineers and Architects
  • Data Scientists and MLOps Engineers
  • Risk, Compliance, and Audit Managers
  • Product and Program Managers
  • Quality Assurance and Reliability Leads

Program Modules:
Module 1: Bias & Data Integrity Foundations

  • Recognize bias sources in data.
  • Assess sampling and coverage.
  • Improve labeling quality.
  • Detect drift in inputs.
  • Apply dataset documentation.
  • Plan mitigation early.

Module 2: Fairness Metrics & Evaluation

  • Select group and individual metrics.
  • Analyze subgroup and intersectional effects.
  • Balance parity and performance.
  • Calibrate thresholds responsibly.
  • Validate with holdout cohorts.
  • Report residual risks clearly.

Module 3: Robustness & Security Engineering

  • Test against adversarial behaviors.
  • Harden models and features.
  • Detect out-of-distribution inputs.
  • Run stress and chaos tests.
  • Secure data and model artifacts.
  • Integrate controls into MLOps.

Module 4: Transparency & Explainability

  • Produce model and system cards.
  • Use interpretable techniques.
  • Communicate uncertainty.
  • Provide user-facing rationale.
  • Trace data, code, and decisions.
  • Maintain change logs.

Module 5: Governance, Risk & Compliance

  • Map controls to NIST AI RMF.
  • Align processes with ISO/IEC 42001.
  • Define roles and accountability.
  • Maintain risk and control registers.
  • Prepare audit-ready evidence.
  • Conduct impact assessments.

Module 6: Lifecycle Operations & Assurance

  • Monitor quality and fairness in prod.
  • Set alerts and escalation paths.
  • Handle incidents and rollbacks.
  • Manage updates and re-training.
  • Review human-in-the-loop steps.
  • Publish periodic assurance reports.

Exam Domains:

  1. Bias Identification and Data Integrity
  2. Fairness Measurement and Decision Policies
  3. Adversarial Robustness and Secure AI Engineering
  4. Transparency, Explainability, and Documentation
  5. Governance, Risk, and Compliance for Trustworthy AI
  6. Operational Monitoring, Incident Response, and Assurance

Course Delivery:
The course is delivered through lectures, interactive discussions, and project-based learning led by experts in trustworthy AI. Participants access online resources, readings, case studies, and guided tools to practice methods aligned to C-TAIP.

Assessment and Certification:
Participants are assessed through quizzes, assignments, and a capstone project. Upon successful completion, participants receive the Certified Trustworthy AI Professional (C-TAIP) certificate.

Question Types:

  • Multiple Choice Questions (MCQs)
  • Scenario-based Questions

Passing Criteria:
To pass the Certified Trustworthy AI Professional (C-TAIP) Certification Training exam, candidates must achieve a score of 70% or higher.

Ready to lead with trustworthy AI? Enroll today. Build systems people rely on. Earn the C-TAIP credential with Tonex.

Request More Information