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AI Governance and Privacy Professional Certification (AIGP) · LearnSpace
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courseraIT и технологии

AI Governance and Privacy Professional Certification (AIGP)

Курс от Packt
Средний≈ 15.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Build the knowledge needed to govern AI systems responsibly, manage privacy risks, and prepare for AIGP certification. You will learn how AI systems work, why they create new accountability challenges, and how governance frameworks support trustworthy AI. The course begins with the AIGP exam structure, core AI concepts, machine learning foundations, OECD classification, socio-technical systems, data governance, intellectual property, and third-party AI risk. You will then explore AI harms, responsible AI principles, privacy law requirements, automated decision-making, organizational governance models, stakeholder engagement, risk assessment, and development lifecycle controls. Later modules focus on deployment governance, monitoring, model drift, incident response, agentic AI, vendor oversight, the EU AI Act, global AI laws, GDPR, DPIAs, ISO standards, non-discrimination, consumer protection, and product liability. This intermediate course is ideal for privacy, compliance, legal, risk, security, product, and technology professionals. Basic familiarity with AI, privacy, or governance concepts is helpful. By the end of the course, you will be able to evaluate AI risks, apply responsible AI principles, support governance programs, interpret major AI regulations, and prepare for AIGP-style exam questions.

Навыки, которые вы освоите

Responsible AIRegulation and Legal ComplianceData GovernanceGeneral Data Protection Regulation (GDPR)GovernanceLaw, Regulation, and ComplianceRisk ManagementGovernance Risk Management and ComplianceArtificial Intelligence and Machine Learning (AI/ML)RiskingLegal RiskData EthicsDecision IntelligenceMachine LearningAI SecurityInformation PrivacyModel DeploymentPersonally Identifiable InformationAI literacyCompliance Management

Программа курса

8 модулей · 150 учебных материалов

01Introduction5 материалов

Introduction

Your Path to Becoming an AI Governance LeaderВидеоIntroduction to the AIGP CertificationВидеоUnderstanding the AIGP Body of KnowledgeВидеоBloom's Taxonomy and Your Exam QuestionsВидеоThe Four Domains of the AIGP Exam

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Packt - Course Instructors

Преподаватель курса

AI Governance and Privacy Professional Certification (AIGP)
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 15.5 ч

8 модулей

Язык: Английский

Часть программы вашего университета
Видео
02Understanding Foundation of AI25 материалов

Understanding Foundation of AI

What Is Artificial IntelligenceВидеоTraits of AI SystemsВидеоAI's Impact on Decision-MakingВидеоClassifying AI Systems – The OECD FrameworkВидеоTypes of AI - ANI, AGI, ASIВидеоSupervised, Unsupervised, Reinforcement LearningВидеоDeep Learning and Neural Networks ExplainedВидеоMachine Learning in the Real World - Risks and BenefitsВидеоWhat Is a Socio-Technical SystemВидеоHuman, Organizational, and Technical LayersВидеоEmergent Behaviour's and UnpredictabilityВидеоAccountability in Complex AI SystemsВидеоIntroduction to the OECD AI ClassificationВидеоUse-Case Based Categorization of AIВидеоApplying the OECD Model in PracticeВидеоOpen-Source Models and Cloud EcosystemsВидеоCompetitive Pressure and AI AccelerationВидеоThe Geopolitics of AI InnovationВидео[BOK 2.1] Data Governance Policies for AI SystemsВидео[BOK 2.1] Intellectual Property Considerations in AI DevelopmentВидео[BOK 2.1] Third-Party Risk Assessment Documents and ContractsВидео[BOK 2.1] Acceptable Use Policies for Third-Party AI SystemsВидео[BOK 2.1] AI Models vs. AI Systems - Governance DistinctionsВидеоUnderstanding AI Systems vs. AI Models: Governance ImplicationsDIALOGUEUnderstanding Foundation of AI - AssessmentЗадание
03AI Impacts on People and Responsible AI Principles30 материалов

AI Impacts on People and Responsible AI Principles

The Landscape of AI-Induced HarmsВидеоTaxonomies of Harm Frameworks for IdentificationВидеоIndividual Harms Part 1 - Bias and DiscriminationВидеоIndividual Harms Part 2 - Civil Rights and Privacy ConcernsВидеоGroup Harms Surveillance and Systemic DisadvantageВидеоSocietal Harms Threats to Democracy and Public SafetyВидеоOrganizational and Environmental HarmsВидеоOperational and Business RisksВидеоPrivacy Risks in the AI LifecycleВидеоThe Bedrock of Trust OECD and Fair Information Practices (FIPs)ВидеоThe Five OECD Principles for Trustworthy AIВидеоIdentifying Key Ethical Issues for AIВидеоFoundational Controls to Mitigate Ethical RiskВидеоCreating a Culture of Ethical AI Within an OrganizationВидеоThe Four Characteristics of Trustworthy AIВидеоHow to Achieve Trustworthy AI An Operational FrameworkВидеоOperationalizing Responsible AI PracticesВидеоFostering a Culture of Responsible AIВидео[Bok 2.1] Transparency Requirements Under Data Privacy LawsВидео[Bok 2.1] Lawful Basis for Processing Data in AI SystemsВидео[Bok 2.1] Automated Decision-Making Rules - GDPR Article 22Видео[Bok 2.1] Explainability and Contestability in Automated DecisionsВидео[Bok 2.1] South Korean AI Basic Law - OverviewВидео[Bok 2.1] South Korean AI Basic Law - Compliance RequirementsВидео[Bok 2.1] U.S. State-Level AI Legislation - Colorado and CaliforniaВидео[Bok 2.1] U.S. State-Level AI Legislation - Sector-Specific LawsВидео[Bok 2.1] ISO/IEC 42005 - AI Management System GovernanceВидео[Bok 2.1] ISO/IEC 42005 - Implementation and ControlsВидеоAI Governance, Law, and Transparency in PracticeDIALOGUEAI Impacts on People and Responsible AI Principles - AssessmentЗадание
04Responsible AI Governance and Risk Management19 материалов

Responsible AI Governance and Risk Management

Tailoring AI Governance to Your OrganizationВидеоThe Three Key Roles Developers, Deployers, and UsersВидеоPolicies for Oversight and AccountabilityВидеоIdentifying Key Stakeholders in AI GovernanceВидеоThe Importance of Cross-Functional Collaboration in AI GovernanceВидеоGaining Leadership Support for AI GovernanceВидеоBuilding a Formal AI Governance StructureВидеоExploring Different AI Governance ModelsВидеоA Framework for Engaging StakeholdersВидеоCreating AI Literacy_ Training and Awareness for StakeholdersВидеоAligning AI Risk with Broader Risk Management StrategiesВидеоEstablishing AI Assessment ProcessesВидеоContext-Specific AI Risk AssessmentВидеоEvaluating Outcomes Is the AI Performing as DesiredВидеоThe NIST AI Risk Management Framework (RMF) and ARIA ProgramВидео[BOK 2.1] AI System vs. AI Model Development GovernanceВидео[BOK 2.1] Data Governance in AI DevelopmentВидеоModel vs. System Governance in AI DevelopmentDIALOGUEResponsible AI Governance and Risk Management - AssessmentЗадание
05Governing AI Development16 материалов

Governing AI Development

The AI System Development Life CycleВидеоDefining the Business Problem and Use CaseВидеоConducting Impact Assessments for AIВидеоHuman Oversight and Operational Controls in AI DevelopmentВидеоApplying Risk Assessment Strategies in DevelopmentВидеоDesigning the System Architecture and Evaluating PerformanceВидеоThe Importance of Training, Testing, and ValidationВидеоDocumenting the Development ProcessВидеоKey Questions for Data and Jurisdictional RequirementsВидеоEstablishing Data Lineage and ProvenanceВидеоEnsuring Data Quality and Proper FormattingВидеоThe Five V's of Data Wrangling and PreparationВидеоKey Considerations in Data PreparationВидеоSelecting and Engineering Model FeaturesВидеоGoverning the AI Development Life CycleDIALOGUEGoverning AI Development - AssessmentЗадание
06Governing AI Deployment20 материалов

Governing AI Deployment

The Final Step Deploying the AIВидеоUpdating Privacy and Security Policies for AIВидеоUnderstanding AI Deployment RequirementsВидеоUnique Challenges of Deploying Proprietary AI ModelsВидеоManaging Third-Party AI RiskВидеоEvaluating Vendor and Open Source AgreementsВидеоAssessing Readiness for ProductionВидеоPeriodic Assessment of the Deployed AI ModelВидеоMonitoring AI Systems for Risks and MitigationsВидеоManaging Model Drift and IterationВидеоIncident Response for Deployed AI SystemsВидеоDisclosures, Transparency, and AccountabilityВидео[BOK 2.1] Agentic Architectures and Autonomous AI Systems - OverviewВидео[BOK 2.1] Agentic Systems - Governance Challenges and OversightВидео[BOK 2.1] Real-World Applications and Governance of Agentic AIВидео[BOK 2.1] AI Model Monitoring and Performance ManagementВидео[BOK 2.1] Enhanced Third-Party AI Risk ManagementВидео[BOK 2.1] AI APIs and SaaS Tools - Governance RequirementsВидеоGoverning Agentic AI Systems: Oversight, Risk, and AccountabilityDIALOGUEGoverning AI Deployment - AssessmentЗадание
07The EU AI Act16 материалов

The EU AI Act

What is the EU AI Act and Why is it ImportantВидеоThe Global Impact and Applicability of the EU AI ActВидеоExemptions to the EU AI ActВидеоKey Roles Defined in the Act Provider, Deployer, Importer, and Deployer,ImporterВидеоThe AI Literacy RequirementВидеоThe Four Risk Levels Under the EU AI ActВидеоProhibited AI SystemsВидеоHigh-Risk AI Systems Definition and RequirementsВидеоObligations for Providers of High-Risk AIВидеоObligations for Deployers of High-Risk AIВидеоLimited-Risk and Minimal-Risk AI SystemsВидеоGoverning General-Purpose AI (GPAI) ModelsВидеоThe Governance and Enforcement Structure of the ActВидеоPenalties and the Enforcement TimeframeВидеоNavigating the EU AI Act: Roles, Risks, and Real-World ScenariosDIALOGUEThe EU AI Act - AssessmentЗадание
08Other Laws and Standards Related to AI19 материалов

Other Laws and Standards Related to AI

The Global Landscape of AI RegulationВидеоAI Regulation in the United States Federal and State GuidanceВидеоAI Regulation Around the World China, Canada, and BeyondВидеоBuilding a Flexible AI Governance FrameworkВидеоKey International Standards ISO 22989 and ISO 42001ВидеоThe HUDERIA Framework A Human Rights-Based ApproachВидеоApplying Core Data Privacy Principles to AIВидеоThe Intersection of the GDPR and AIВидеоUsing Anonymized and Pseudonymized Data in AIВидеоThe Role of DPIAs and Conformity Assessments in AI GovernanceВидеоHandling Sensitive and Special Categories of Data in AIВидеоObligations on Data Controllers When Using AIВидеоHow Current Laws Apply to AI SystemsВидеоIntellectual Property (IP) Legislation and AIВидеоNon-Discrimination Laws and AIВидеоConsumer Protection and Product Liability Laws in the Age of AIВидеоOther Laws and Standards Related to AI - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание