Enterprise Cloud & AI Security Governance Certification

Certified Enterprise Cloud and AI Security Governance Training

Governance that Secures Cloud and AI

Govern end-to-end Cloud and AI systems across data, identity, workloads, and models

Implement governance controls using IAM, encryption, monitoring, and cloud-native policies

Apply global governance frameworks including ISO/IEC 42001, NIST AI RMF, EU AI Act, and CSA AICM

Assess AI risk, compliance readiness, and governance assurance in cloud environments

About Course

InfosecTrain's Certified Enterprise Cloud and AI Security Governance Training is a comprehensive, governance-driven program designed to help professionals secure and govern cloud and AI environments at an enterprise scale. The course provides a structured understanding of how cloud platforms and AI systems operate, and how security, risk management, compliance, and accountability must be governed across their full lifecycle.

The program covers cloud computing and AI foundations, followed by deep dives into cloud and AI security governance, risk assessment, compliance, audit, IAM, data governance, workload security, monitoring, application security, and incident response. Learners will gain practical insight into governing AI data, identities, pipelines, models, and monitoring using cloud-native controls.

Aligned with global frameworks such as ISO/IEC 42001, NIST AI RMF, EU AI Act, and CSA AICM, this course prepares participants to design defensible governance models, conduct AI risk and compliance assessments, manage AI-specific incidents, and support responsible AI initiatives across enterprises, regulated industries, and government environments.

Course Curriculum

MODULE 1

Cloud Computing Concepts & Architecture

Cloud Computing Overview
Essential characteristics, benefits, and challenges
Abstraction & Orchestration
Cloud Service Models & Deployment Models
CSA Enterprise Architecture Model
Cloud Security Overview
Shared Security Responsibility Model
Scope, Responsibilities & Models
Threat landscape and new attack vectors in cloud

MODULE 2

AI Concepts & Architecture

Fundamentals of Artificial Intelligence & Machine Learning
AI Systems Classification
Types of AI
AI Usage & Impact
Use Cases, Benefits & Challenges
AI Governance Foundation
AI Model Types
Training Types
AI Technology Stack
AI Impact & Principles

MODULE 3

Introduction to Cloud & AI Security Governance

Foundations of Cloud & AI Security Governance
- Objectives of Governance vs. Security
- Enterprise Risk Governance in Cloud & AI
- Cloud Security Frameworks & Policies
Complexities in Cloud & AI Security Governance
- Governance as a Business Enabler
- Impact of Cloud Service & Deployment Models
- Cloud Risk Trade-offs & Governance Tools
Shared Responsibility & Governance Enablers
- Contracts, SLAs & PLAs
- Roles & Critical Stakeholders in Cloud & AI Governance
Cloud & AI Threat Landscape
- Cloud-specific Threats & Attack Vectors
- AI threat landscape
- Defense-in-depth Approach
Security Controls Across Cloud & AI Lifecycle
- Encryption, IAM & Intrusion Detection
- AI lifecycle Security Controls
AI Red Teaming & Adversarial Attacks
- Incident Response for AI Systems
- Case Study
- Capital One Cloud Data Breach – Governance Failures

MODULE 4

Risk Assessment and Management

Cloud-Specific Risks & Threats
- Data Breaches, Data Loss, and Multi-tenancy
- Misconfigurations, and Shared Resource Risks
- Real-world Cloud Security Incident Case
Cloud Risk Assessment Methodologies
- Cloud Risk Assessment Process
- NIST Cybersecurity Framework for Cloud
- Risk Register Development
Cloud Risk Treatment & Control Selection
- Risk Acceptance, Avoidance, Transfer, and Mitigation
- Cloud Security Control Selection
- Vendor & Third-party Cloud Risk Assessment
Cloud Risk Monitoring & Continuous Improvement
- Cloud Security Metrics & KPIs
- SIEM in Cloud Environments
- Incident Management & Cloud Security Policy Basics
AI Risk Categories
- Ethical, operational, societal risks
AI Risk Frameworks & Models
- NIST AI RMF
- MIT AI Risk Repository
- EU AI Act risk tiers
AI Risk Assessment & Governance
- AI Risk Register & AI Impact Assessment (AIIA)
- Bias Identification & Mitigation
- Third-party AI Risk Management
- AI Governance Maturity Models
Case Studies
- Cloud Risk Assessment & Sample Risk Report
- AI-powered chatbot risk assessment

MODULE 5

Cloud & AI Compliance, Audit & Assurance

Cloud Compliance Program Overview
Designing & Building a Cloud Compliance Program
Cloud-Relevant Laws & Regulations (Overview)
Implementing Compliance Controls in Cloud Environments
Compliance Inheritance & Shared Responsibility
Compliance Artifacts & Evidence Management
Cloud Auditing Fundamentals
Audit Characteristics, Principles & Criteria
- Types of Audits
- Audit Steps, Objectives & Scope
Auditing & Reporting in the Cloud
- Cloud Auditing Standards & Frameworks
Auditing AI Systems
- AI Audit Frameworks & Standards
- Key AI Audit Areas & Techniques
- Challenges in AI Auditing (Models, Data Access, Transparency)
Practical Exercises & Case Studies
- PCI DSS Compliance in Cloud
- AI Audit Simulation Exercise

MODULE 6

Organization Management

Organization Hierarchy Models
- Organization Capabilities Within a Cloud Service Provider
- Building a Hierarchy Within a Provider
Managing Organization-Level Security Within a Provider
- Identity Provider & User/Group/Role Mappings
- Common Organization Shared Services
Considerations for Hybrid & Multi-Cloud Deployments
- Organization Management for Hybrid Cloud Security
- Organization Management for Multi-Cloud Security
- Organization Management for SaaS Hybrid & Multi-Cloud

MODULE 7

Identity and Access Management (IAM) for Cloud & AI

Foundations of IAM in Cloud & AI
- IAM Concepts, Components & Importance
- IAM Across Major Cloud Platforms
- RBAC, ABAC & PBAC Models
Roles, Permissions & Access Governance
- Role Design, Hierarchy & Inheritance
- Least Privilege & Authorization Creep Prevention
Federation, SSO & MFA
- Federated Identity & Cloud Integration
- SO & MFA Best Practices
Zero Trust for Cloud & AI
- Zero Trust Principles
- Continuous Authentication & Least Privilege
- Zero Trust Implementation in Cloud & AI Systems
IAM for AI Workloads
- Human vs Machine Identities
- Service Accounts & Model Access Control
- API & Inference Access Governance
Case Study
- Best Practices & IAM Baselining in Cloud Environments

MODULE 8

Cloud & AI Data Security, Privacy & Governance

Strategic Role of Data in Cloud & AI Systems
Enterprise Data Strategy for AI
Cloud Storage Types for AI Workloads
- Storage Models (Object, Block, File)
- Use Cases & Selection Criteria
Data Governance Policy Framework
- Data Ownership & Stewardship
- Data Quality & Data Gathering
- Data Lifecycle Management for AI Projects
Data Lineage, Traceability & Regulatory Mapping
Data Cleansing, Labelling & Ethics
- Data Quality Improvement
- Data Labelling Risks
- Data Ethics & Responsible Data Use
Data Bias in AI Systems
- Data Validation & Testing
Data Security Tools & Techniques
- Data Classification
- Identity & Access Management
- Access Policies
- Encryption & Key Management
- Data Loss Prevention (DLP)
Building a Cloud Data Classification Program
- Policy Establishment
- Monitoring & Enforcement
Data Privacy & Protection for AI
- Data Anonymization & Pseudonymization
- Differential Privacy Techniques
- Data Exfiltration Risks
Data Sovereignty, Residency & Cross-Border Governance
- Legal & Compliance Implications
- Data Localization & Geo-Fencing
- Regional Regulatory Compliance (eg: GDPR)
Data Dispersion, Replication & Resiliency Governance
- Multi-Region Replication & DR
- Governance Concerns on Location & Access
- Contractual, SLA & Audit Controls
Data Encryption & Key Management Best Practices
- Encryption Standards & Algorithms
- Key Lifecycle Management
- Cloud Provider Key Management Services
Data Retention, Deletion & Archiving Policies
- Secure Data Erasure
- Lifecycle Automation
- Legal Hold Challenges
Key Cloud & AI Data Governance Risks
- Data Poisoning
- Data Leakage & Exfiltration
- PII Misuse
- Cross-Border Data Violations
Data Security for AI & AI as a Service (AIaaS)
Case Studies
- Securing Sensitive Data in Cloud Object Storage
- AI Recommendation Engine - End-to-End Data Governance

MODULE 9

Cloud Infrastructure & Networking

Cloud Network Architecture & Security Foundations
- Virtual Networks, Isolation & Segmentation
- Security Groups, NACLs & Firewall Concepts
- Software-Defined Networking (SDN)
Network Segmentation & Zero Trust Networking
- Segmentation & Zoning Strategies
- Zero Trust Network Access (ZTNA)
Cloud Firewalls & Application Protection
- Cloud Firewall Services
- Web Application Firewall (WAF)
DDoS & Network Attack Protection
- DDoS Attack Concepts
- Cloud DDoS Mitigation Services
- Detection & Response Strategies
Zero Trust & Secure Network Access Models
- Software-Defined Perimeter
- Secure Access Service Edge (SASE)

MODULE 10

Cloud Workload Security

Types of Cloud Workloads
Impact on Workload Security Controls
Securing Virtual Machines
- Virtual Machine Challenges & Mitigations
- Creating Secure VM Images with Factories
- Snapshots & Public Exposures/Exfiltration
Securing Containers
- Container Images
- Container Network Architecture
- Container Orchestration & Management Systems
- Container Orchestration Security
- Runtime Protection for Containers
Securing Serverless and Function as a Service
- FaaS Security Issues
- IAM for Serverless
- Environment Variables & Secrets
Securing AI Workloads
AI-System Threats
AI Risk Mitigation and Shared Responsibilities

MODULE 11

Security Monitoring

Role of Security Monitoring in Cloud & AI Governance
Cloud Monitoring Fundamentals
- Logs, Metrics & Events
- Security vs Operational Monitoring
Cloud Telemetry Sources
- Management Plane Logs
- Service & Application Logs
- Resource-Level Logs
- Cloud-Native Monitoring Tools
Log Collection & Monitoring Architectures
- Centralized Log Collection
- Log Storage & Retention Governance
- Cascading / Multi-Account Log Architecture
Beyond Logs - Security Posture Management
- Cloud Security Posture Management (CSPM)
- Configuration Drift Detection
- Continuous Compliance Monitoring
AI for Security Monitoring
- AI-Driven Threat Detection
- Behavioural Analytics
- Anomaly Detection in Cloud Environments
Alerting & Automated Response Governance
- Security Alert Orchestration
- Event-Driven Response Models
- Notification, Escalation & Auditability
Monitoring Risks & Governance Challenges
- Log Tampering
- Alert Fatigue
- Blind Spots in Multi-Cloud & AI Workloads

MODULE 12

Application Security

Secure Development Lifecycle (SDLC)
- SDLC Stages
- Threat Modelling
- Pre-Deployment & Post-Deployment Security Testing
SDLC Methodologies
- Agile, DevOps, Waterfall
Governance in Each SDLC Phase
- Planning, Design, Development, Testing, Deployment, Maintenance
Architecture's Role in Secure Cloud Applications
- Cloud Impacts on Application Security
- Architectural Resilience
Identity & Access Management in Application Security
- Secrets Management
DevOps & DevSecOps Integration
SDLC for AI Systems
- Secure AI Model Development Lifecycle
- Governance Across AI Training, Testing & Deployment

MODULE 13

Incident Response

Role of Incident Response in Cloud & AI Governance
Incident Response Lifecycle
- Preparation, Detection, Containment, Eradication, Recovery, Lessons Learned
Cloud-Specific Incident Response Planning
- Shared Responsibility
- Testing, Table-Top & Simulation Exercises
Cloud Incident Investigation & Triage
- Incident Classification
- Impact Assessment
- Business vs Technical Prioritization
Evidence Collection & Cloud Forensics
- Logs & Digital Artifacts
- Evidence Preservation
- Data Integrity & Chain of Custody
Digital Forensics in Cloud Environments
- Shared Infrastructure & Multi-Tenant Challenges
- Cloud Forensics Best Practices
AI-Specific Security Incidents
- Data Leakage vs Model Inversion
- Model Drift
- Adversarial & Prompt-Based Attacks
AI Incident Playbook Design
- Detection & Response
- Model Isolation & Rollback
- Dataset & Pipeline Integrity Validation
Incident Communication & Governance
- Executive, Regulatory & Legal Reporting
Scenario Discussion
- Designing a Cloud & AI Incident Response Runbook

MODULE 14

Application Security

Overview of Global AI Laws & Regulations
- Legal & Ethical Foundation
- Data Privacy, Bias, Transparency & Accountability
Categories of AI Law & Regulatory Approaches
- Emerging Trends in AI Legislation
- Industry Impact of AI Regulations
Key Global AI Frameworks & Standards
- OECD AI Principles
- EU AI Act
- ISO/IEC 42001:2021
Regulatory Impact Assessment on AI Systems
- Cross-Border AI Compliance Management
Intellectual Property Rights in AI
- Copyright & Patents for AI Models & Data
- Ownership of AI-Generated Content
Liability & Accountability in AI
- Liability for AI-Related Harms
- Algorithmic Accountability & Auditability
AI System Auditing & Regulatory Review Mechanisms

Target Audience

Information Security Professionals

Cloud Security Architects

Enterprise Risk Management Professionals

Cloud Managers & Platform Owners

Governance, Risk & Compliance (GRC) Professionals

CISOs, Security Managers & IT Directors

Data Protection & Privacy Officers

AI Program Managers & Digital Transformation Leaders

Compliance & Internal Audit Professionals

Technology Risk & Advisory Consultants

Course Objectives

Understand Cloud and AI Architectures and Service Models

Apply Cloud and AI Security Governance Principles

Assess Cloud and AI Risks Using Recognized Frameworks

Design Governance Controls Across Cloud and AI Lifecycles

Implement IAM and Zero Trust for Cloud and AI

Govern AI Data Security, Privacy, and Lineage

Establish Cloud and AI Compliance and Audit Readiness

Monitor AI Drift, Bias, and Security Posture

Respond to Cloud and AI Security Incidents

Interpret Global AI Laws and Accountability Requirements

Words Have Power

Waseem Akram Fareed

Canada

I have pursued CISSP, CRISC, and CISM from InfosecTrain. InfosecTrain is my default option when I think about any cybersecurity certification. The trainer's dedication and sincerity towards his classes is something that inspires me a lot personally. You will get 100 percent from InfosecTrain for whichever course you want to pursue. Especially the trainers are outstanding.

Fuzail Ahmed Lohare

UAE

The trainer was very good, with good knowledge and skills to share, and he handled the session with patience. I really enjoyed the training. Selecting InfosecTrain is always a good choice for me. The sales team is very supportive and helped me on this journey.

Rudraram Sai Kiran

United Kingdom

The trainer is a great presenter/tutor and teaches in a relaxing manner. His sense of humor and honesty about the task ahead for the newbie help make the challenging subject matter accessible. Thank you very much! I had been looking forward to this workshop for weeks, and it exceeded my expectations! I have learned a lot.

Jatin Tandon

Very detailed and organized training, as always, by the best instructors at InfosecTrain. Will come back for more courses after completing my certification.

Yamna Taouss

Morocco

It was an interesting training that could help me succeed in obtaining certificates. I am truly thankful to InfosecTrain for an amazing training. Looking forward to attending more sessions with InfosecTrain.

Certified Enterprise Cloud and AI Security Governance Training

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About Course