Artificial Intelligence Governance Professional (AIGP)

Overview

Master AI Governance, Ethics & Compliance | AIGP Certification | AI Risk Management & Responsible AI Practices What you'll learn:

Policy Makers – Develop AI governance frameworks that align with legal and ethical standards.Compliance Officers – Ensure AI systems comply with global regulatory requirements and industry best practices.Business Executives – Understand the risks and opportunities of AI governance in corporate decision-making.Data Scientists – Implement AI models that adhere to fairness, transparency, and accountability principles.Legal Professionals – Analyze AI-related laws, regulations, and liability concerns in various jurisdictions.Cybersecurity Experts – Mitigate risks related to AI security, data privacy, and adversarial attacks.AI Researchers – Incorporate responsible AI principles into research and development processes.Product Managers – Design AI-driven products with governance, compliance, and ethical considerations in mind.Educators & Trainers – Teach AI governance principles to students and professionals effectively.Investors & Venture Capitalists – Assess AI startups for ethical risks, governance maturity, and regulatory compliance. Why You Should Take the Artificial Intelligence Governance Professional (AIGP) TrainingIn today’s rapidly evolving AI landscape, businesses and institutions need experts in AI Governance, Ethics & Compliance who can evaluate AI systems, curate standards, and implement strategies for adhering to AI regulations.The AIGP Certification training equips professionals with the knowledge and skills to develop, integrate, and deploy trustworthy AI systems in alignment with emerging laws, policies, and AI risk management frameworks.What You Will Learn:

Master AI Governance, Ethics & Compliance by understanding core AI risks and ethical principles.Explore AI Risk Management strategies to mitigate potential harms and regulatory violations.Learn about different AI technology stacks and their applications.Identify key AI frameworks & policies that govern responsible AI deployment.Understand AI strategy development and implementation of AI governance policies.Assess AI models using risk assessment methodologies and compliance frameworks.Navigate existing and emerging AI laws, including GDPR, the EU AI Act, and liability reform.Study how intellectual property laws, non-discrimination laws, and consumer protection laws apply to AI systems.Gain hands-on insights into governing AI design, data collection, model testing, and deployment decisions.Get Certified and Advance Your CareerMaster the 4 domains of the IAPP AIGP Certification exam with 3+ hours of on-demand video.Prepare for the 2025 AIGP Certification Exam with expert-led training.Understand the technological foundations of AI and its societal impact.Develop a strong foundation in responsible AI governance & risk management frameworks.Stay ahead of AI compliance regulations and best practices for responsible AI deployment.This training is designed for professionals who want to lead in AI governance and ensure compliance with AI laws and ethical standards.

Whether you’re an AI strategist, compliance officer, or tech leader, this course will provide the practical skills and knowledge needed to succeed in the evolving AI regulatory landscape.

Syllabus

• Introduction to AI Governance
Overview of AI governance, ethics, and compliance
Importance of AI governance in modern enterprises
• Core Principles of Responsible AI
Fairness, transparency, and accountability in AI systems
Ethical considerations and decision-making
• Legal and Regulatory Frameworks
Key regulations: GDPR, EU AI Act, and global AI laws
Intellectual property, non-discrimination, and consumer protection laws
Navigating liability and regulatory compliance
• AI Risk Management
Identifying and mitigating AI-related risks
Risk assessment methodologies and compliance frameworks
Strategies for regulatory and ethical risk management
• AI Technology Stacks and Applications
Understanding different AI technologies and their applications
Responsible AI design and implementation strategies
• Governance Frameworks for AI Deployment
Developing AI governance policies and frameworks
Aligning AI applications with legal and ethical standards
• AI Compliance in Corporate Decision-Making
Integrating AI governance in business strategies
Assessing governance maturity in AI startups
• Data Privacy and Security in AI
Mitigating data privacy concerns and adversarial threats
Ensuring cybersecurity in AI deployments
• AI Policy Development and Implementation
Crafting AI strategies that reflect governance and compliance needs
Developing industry best practices for AI governance
• Intellectual Property and AI
Understanding the intersection of AI and intellectual property
Managing IP rights in AI-driven innovations
• Preparing for the AIGP Certification Exam
Exam structure and content
Study tips and resources for certification success
• Hands-on Insights and Case Studies
Practical examples of AI governance challenges
Evaluating and governing AI models, data, and deployment processes
• AI Governance in Practice
Teaching AI governance principles
Role-play and scenario analysis for better understanding
• Stakeholder Engagement in AI Governance
Collaborating with policymakers, legal professionals, and educators
Ensuring multi-disciplinary approaches to AI governance

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Taught by

Pavan Kumar and Avnish Singh

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Subjects

Computer Science