VOOZH about

URL: https://www.coursera.org/learn/ai-governance-regulation

⇱ AI Governance & Regulation | Coursera

AI Governance & Regulation

Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.

AI Governance & Regulation

This course is part of multiple programs.

Instructor: Edureka

Included with

Ask Coursera

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the core principles of AI governance, including roles, frameworks, and regulatory foundations.

  • Analyze AI systems using global governance frameworks to identify risks and compliance requirements.

  • Apply governance practices such as policy design, risk registers, and lifecycle controls in real-world scenarios.

  • Evaluate AI systems through monitoring, auditing, and incident response to ensure responsible and compliant operation.

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

May 2026

Assessments

11 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

This course introduces the foundations and practical implementation of AI governance, helping organizations design and manage responsible AI systems.

You’ll begin by understanding core governance concepts, stakeholder roles, and how governance differs from ethics and compliance. The course then explores global frameworks such as the EU AI Act and NIST AI RMF, enabling you to align AI systems with regulatory expectations. Next, you’ll learn how to operationalize governance through policy design, maturity models, and lifecycle risk management using tools like risk registers and impact assessments. The course also covers monitoring, auditing, and incident response to ensure continuous oversight of AI systems. By the end of this course, you will be able to: - Explain AI governance fundamentals and stakeholder roles - Apply global frameworks to real-world AI systems - Design policies and manage lifecycle risks - Monitor, audit, and respond to AI risks Designed for professionals, analysts, and anyone working with AI systems, this course provides a structured approach to implementing AI governance in practice. To be successful, learners should have a basic understanding of AI concepts and business processes. Start your journey into responsible AI and learn how to build governance systems that ensure accountability and trust.

Explore how AI governance is structured within modern enterprises and aligned with global regulatory expectations. This module covers foundational governance concepts, stakeholder role design, and leading frameworks like the EU AI Act, NIST AI RMF, and ISO standards, enabling structured, compliant, and risk-aware AI system management.

What's included

10 videos3 readings3 assignments

10 videos•Total 54 minutes
  • Course Introduction: AI Governance and Regulation •5 minutes
  • AI Governance Foundations•5 minutes
  • The Trinity: Ethics, Compliance, and Governance•4 minutes
  • AI Governance Stakeholders and Role Architecture•7 minutes
  • Governance Role Mapping Using RACI Framework•7 minutes
  • EU AI Act: Risk Tiers and Compliance Essentials•5 minutes
  • NIST AI RMF Lifecycle - Govern, Map, Measure, Manage•6 minutes
  • Global AI Governance - ISO 42001 and International Frameworks•7 minutes
  • AI Regulatory Risk Classification Using EU AI Act Logic•4 minutes
  • NIST AI RMF Coverage Assessment and Gap Analysis•5 minutes
3 readings•Total 30 minutes
  • Course Syllabus: AI Governance and Regulation•10 minutes
  • AI Governance Foundations: Roles, Responsibilities, and Structures•10 minutes
  • Module Summary: Global Frameworks and Regulatory Strategy•10 minutes
3 assignments•Total 27 minutes
  • Knowledge Check: Global Frameworks and Regulatory Strategy•15 minutes
  • Knowledge Check: AI Governance Fundamentals•6 minutes
  • Knowledge Check: Regulatory Intelligence & Global Frameworks•6 minutes

Learn how to translate AI governance into operational practice through structured risk and policy lifecycle management. This module explores maturity models, policy design, supply chain risk, and lifecycle governance, while enabling systematic risk identification, impact assessment, and control implementation using tools like risk registers and AIA frameworks.

What's included

10 videos2 readings3 assignments

10 videos•Total 63 minutes
  • AI Governance Maturity Models•6 minutes
  • Designing AI Use Policies•7 minutes
  • AI Vendor and Supply Chain Risk•7 minutes
  • Data Lineage and Provenance in AI•5 minutes
  • AI Policy Compliance Linter•6 minutes
  • AI Lifecycle Governance and System Inventory•7 minutes
  • Enterprise Risk Register and Control Framework•8 minutes
  • Algorithmic Impact Assessment and Oversight•6 minutes
  • AI Risk Register and Heatmap Analysis•5 minutes
  • Algorithmic Impact Assessment (AIA) Scoring Tool•6 minutes
2 readings•Total 20 minutes
  • AI Governance Structure and Policy Design Guide•10 minutes
  • Summary: Operationalizing the Risk and Policy Lifecycle•10 minutes
3 assignments•Total 27 minutes
  • Knowledge Check: Operationalizing the Risk, and Policy Lifecycle •15 minutes
  • Maturity, Policy, and Supply Chain•6 minutes
  • AI Lifecycle Governance & Risk Register•6 minutes

Examine how AI governance is enforced through continuous monitoring, auditing, and human oversight, while preparing organizations to manage emerging risks and critical incidents. This module focuses on assurance systems, red-teaming practices, incident response strategies, and integration with enterprise GRC to ensure resilient, accountable, and well-governed AI operations.

What's included

10 videos3 readings3 assignments

10 videos•Total 58 minutes
  • Continuous Monitoring of AI Systems•6 minutes
  • AI Auditing and Conformity Assessment•6 minutes
  • Human Oversight in AI Governance•5 minutes
  • Automated Assurance and Governance Monitoring•6 minutes
  • AI Governance Health Monitoring Dashboard•5 minutes
  • Generative AI Governance - Risk and Control Framework•6 minutes
  • AI Red Teaming in Governance and Risk Assessment•5 minutes
  • AI Red Team Testing and Risk Evaluation•6 minutes
  • AI Incident Response and Remediation•6 minutes
  • Unified AI Governance and Enterprise GRC Integration•6 minutes
3 readings•Total 30 minutes
  • Data Privacy in AI - GDPR, DPDP, and Compliance•10 minutes
  • AI Governance Tools - Platforms and Monitoring Landscape•10 minutes
  • Module Summary: Technical Assurance, Oversight, and Crisis Remediation•10 minutes
3 assignments•Total 27 minutes
  • Knowledge Check: Technical Assurance, Oversight, and Crisis Remediation •15 minutes
  • Assurance, Auditing, and Human Oversight•6 minutes
  • Emerging Risks, Red-Teaming, and Incident Response•6 minutes

Synthesize the complete AI governance journey by connecting strategy, operations, and technical assurance into a unified framework. This module brings together governance design, regulatory alignment, risk lifecycle management, and assurance mechanisms to provide a holistic view of how organizations deploy, manage, and scale responsible AI systems in real-world environments.

What's included

1 video1 reading2 assignments

1 video•Total 3 minutes
  • Course summary: AI Governance and Regulation•3 minutes
1 reading•Total 30 minutes
  • Practice Project: AI Governance Risk and Monitoring Simulation•30 minutes
2 assignments•Total 60 minutes
  • End Course Knowledge Check: AI Governance and Regulation•30 minutes
  • AI Governance Framework Design and Implementation Strategy•30 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Edureka
203 Courses•185,724 learners

Explore more from Data Analysis

Why people choose Coursera for their career

👁 Image

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
👁 Image

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
👁 Image

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
👁 Image

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Frequently asked questions

The course is designed to be completed in approximately 3 weeks, with an estimated 2–3 hours of study per week, including videos, readings, and practice assessments.

It is designed for professionals, analysts, and anyone involved in AI systems or decision-making.

No, a basic understanding of AI concepts is helpful but not mandatory.

You will learn AI governance frameworks, risk management, policy design, and monitoring practices.

The course includes hands-on demos, scenario-based exercises, and governance implementations in Colab.

Yes, the course includes practical scenarios such as risk assessment, policy evaluation, and incident response.

No, the course focuses on governance concepts and structured implementation rather than coding. But knowing basic python can help in better understanding hands-on demonstrations.

Google Colab and structured datasets are used for demonstrations and exercises.

This course focuses on governing AI systems rather than building models.

Yes, the course covers frameworks like the EU AI Act, NIST AI RMF, and ISO standards.

It equips you with in-demand skills in AI governance, risk, and compliance for modern organizations.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.