Professional Certification Program

Certified Responsible AI Analyst

A practical certification designed to help professionals assess, govern, and deploy AI systems responsibly by managing bias, risk, transparency, ethics, and regulatory expectations.

⚖️
Ethical AI Foundations
Understand fairness, accountability, transparency, and human-centric AI principles.
🔍
AI Risk & Bias Management
Identify, assess, and mitigate AI model risks and unintended bias.
🛡️
Governance & Compliance
Align AI systems with global regulations, standards, and responsible AI frameworks.

What you will learn

Build Trustworthy AI
with Confidence

In Certified Responsible AI Analyst, you will gain the skills to assess, govern, and deploy AI systems responsibly. This course equips you to manage AI risks, bias, transparency, and compliance while ensuring ethical and trustworthy AI outcomes.

  • ✔ Understand responsible and ethical AI principles including fairness, accountability, and transparency.
  • ✔ Identify, assess, and mitigate AI risks such as bias, model drift, and unintended consequences.
  • ✔ Apply governance frameworks and controls to manage AI systems across their lifecycle.
  • ✔ Align AI use cases with regulatory expectations and global responsible AI standards.
  • ✔ Evaluate AI models for explainability, transparency, and human oversight.
  • ✔ Support organisations in deploying AI that is trustworthy, compliant, and sustainable.
Professionals evaluating responsible and ethical AI governance frameworks

There are 5 modules in this course

Certified Responsible AI Analyst (CRAA) is designed to equip senior leaders to evaluate, monitor, and report on enterprise AI systems—ensuring fairness, compliance, and continuous oversight through measurable, regulation-ready Responsible AI controls.

Foundations of Responsible AI
Module 1  •  3 lessons
Module details

Build a strong baseline on Responsible AI fundamentals and why they matter for enterprise adoption. You’ll cover the essential principles and the key global standards shaping responsible, compliant AI programs.

What's included
▶
3 lessons
▶
3 lessons
• Total 3 lessons
  • AI fundamentals and enterprise implications
  • Core principles: fairness, accountability, transparency, privacy
  • Global regulatory landscape and standards (EU AI Act, OECD, industry codes)
Detection & Measurement
Module 2  •  3 lessons
Module details

Learn how to detect and measure AI risks using practical methods leaders can apply. You’ll understand bias measurement, data governance essentials, and the KPIs used to track model trustworthiness in production.

What's included
▶
3 lessons
▶
3 lessons
• Total 3 lessons
  • Bias measurement and techniques for non-technical leaders
  • Data quality, provenance and labeling governance
  • Metrics and KPIs for trustworthiness (fairness, robustness, privacy loss)
Governance, Policy & Risk Management
Module 3  •  3 lessons
Module details

Put the right guardrails in place: governance structures, policies, and risk controls that scale. This module covers operating models, assessment routines, and vendor/third-party risk considerations.

What's included
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3 lessons
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3 lessons
• Total 3 lessons
  • AI governance frameworks (roles, committees, escalation paths)
  • Risk assessment, impact assessments (AI / PIA) and controls
  • Procurement, vendor due diligence and third-party model risk
Audit, Assurance & Certification
Module 4  •  3 lessons
Module details

Learn how to evidence Responsible AI in a way auditors, regulators, and boards can understand. You’ll cover audit approaches, operational monitoring, and how to build certification-ready evidence and reporting.

What's included
▶
3 lessons
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3 lessons
• Total 3 lessons
  • Designing internal audits and independent model reviews
  • Operationalizing monitoring, logging and incident response for models
  • Certification checklists, evidence packages and board reporting
Implementation Labs & Case Studies
Module 5  •  3 lessons
Module details

Apply what you’ve learned through realistic scenarios and practical integration work. You’ll run through an incident simulation, review a real case study, and produce an integration roadmap for enterprise governance.

What's included
▶
3 lessons
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3 lessons
• Total 3 lessons
  • Cross-functional tabletop incident simulation and remediation playbook
  • Case study: deploying an explainability program in financial services
  • Roadmap lab: integrating CRAA outputs into enterprise governance
🎓
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

What professionals say about the Responsible AI certification

Ananya S.
AI Risk Analyst, Banking & Financial Services

“This course helped me clearly understand how bias, model risk, and governance connect in real AI systems. I now have a structured way to review AI use cases and challenge teams on explainability and controls.”

Rahul M.
Data Science Manager, Technology Consulting

“We build models all the time, but responsible deployment was a gap. This program gave me practical frameworks to think beyond accuracy and include fairness, transparency, and lifecycle monitoring.”

Sophie L.
Compliance & Governance Lead, AI Products

“What I valued most was how the course translated regulations and ethical principles into operational controls. It helped me communicate Responsible AI expectations clearly to product and engineering teams.”

Daniel K.
Product Owner – AI Platforms, SaaS

“Responsible AI often sounds abstract. This certification made it practical. I now know what questions to ask before deployment and how to document decisions for audits and internal reviews.”

Frequently asked questions

Is this course practical or mostly theoretical?

This course is designed to be applied directly at work. While we explain key concepts, the focus is on real scenarios, decision frameworks, and examples drawn from how organisations actually use AI.

You’ll work through use cases, risks, and trade-offs that leaders and analysts face, not abstract theory.

Do I need a technical or coding background to understand this?

No. This program is built for business, risk, compliance, product, and strategy professionals.

We explain AI concepts in plain language and focus on how to evaluate, govern, and make decisions about AI systems — not how to build models or write code.

How is this different from free AI articles, videos, or webinars?

Free content often explains what Responsible AI is, but not how to apply it inside real organisations.

This course gives you structured frameworks, checklists, and questions you can immediately use when reviewing AI use cases, policies, or projects.

Is this course relevant if my organisation is just starting with AI?

Yes. In fact, this is often the best time to learn Responsible AI.

The course helps you ask the right questions early, avoid common mistakes, and build AI initiatives on stronger foundations before problems arise.

Will this help my career, or is it just another certificate?

The value comes from what you can do after the course, not just the certificate.

You’ll gain the ability to participate confidently in AI discussions, challenge assumptions, and contribute to governance, risk, and strategy conversations — skills that are increasingly in demand.

How much time do I realistically need each week?

Most participants spend around 3–4 hours per week.

The course is self-paced, so you can move faster or slower depending on your workload and revisit sections when needed.

Does the course cover AI risks, ethics, and regulation in a practical way?

Yes. We go beyond principles and focus on how risks, ethics, and regulations translate into real controls, documentation, and decision-making.

This helps you work effectively with legal, compliance, technology, and business teams.

What happens if AI regulations or standards change?

The course focuses on underlying principles and governance approaches that remain relevant even as specific regulations evolve.

This helps you adapt your thinking rather than rely on fixed rules that may change.

Will I receive a certificate after completion?

Yes. After completing the program requirements, you will receive a digital certificate that you can share on LinkedIn, your résumé, or internally.