An Interactive 5-Day Training Course

Artificial Intelligence (AI) Systems Architecture and Governance

08 - 12 Dec 2025
Dubai
| $5950
07 - 11 Dec 2026
Dubai
| $5950

Introduction

This Artificial Intelligence (AI) Systems Architecture and Governance training course is designed for technical leaders shaping the future of enterprise AI systems. In today's rapidly evolving technological landscape, building robust, scalable, and governable AI architectures is crucial for organizational success. This five-day training course equips technical leaders with comprehensive knowledge and practical tools to design, implement, and govern enterprise-grade AI systems.

Drawing from real-world implementations, participants will master the complexities of modern AI systems. The training course integrates current technical standards, cloud-native architectures, and governance frameworks, providing a thorough understanding of building enterprise AI platforms.

Key course outcomes:

Key Learning Outcomes

At the end of this training course, you will learn to:

Training Methodology

This training course combines interactive lectures, group discussions, case studies, and practical exercises to provide a comprehensive learning experience. Participants will engage in thought-provoking discussions, analyze real-world scenarios, and apply the concepts learned to practical situations. The training course facilitator will draw upon extensive industry experience to share best practices and provide personalized guidance to attendees. Throughout the training course, participants will have ample opportunities to network with peers and develop actionable plans for implementing corporate governance improvements within their organizations.

Artificial Intelligence (AI) Systems Architecture and Governance

Who Should Attend?

The Organisation will have the following benefits,

  • Improved AI system reliability and scalability
  • Enhanced technical governance frameworks
  • Better integration of AI systems
  • Reduced technical debt in AI implementations
  • Stronger architecture review processes
  • Increased efficiency in AI deployments
  • Better resource utilization

Learning Journey Breakdown

Architectural Fundamentals

  • Enterprise AI Architecture Patterns
  • Cloud vs On-Premise AI Infrastructure
  • Distributed AI Systems
  • Model Operations (MLOps)
  • Infrastructure Security Standards

Regional Implementation

  • Saudi Cloud First Policy (verified)
  • UAE TRA's actual published guidelines
  • Qatar's documented Cloud Policy
  • South Africa's GPC framework
  • Nigeria's Cloud Computing Policy
  • Architecture decisions
  • Implementation challenges
  • Governance framework

Core Components 

  • Model Development Platforms
  • Data Pipeline Architecture
  • Model Serving Infrastructure
  • Monitoring Systems
  • Version Control for AI 

Integration 

  • API Management
  • Microservices Architecture
  • Container Orchestration
  • Service Mesh Implementation
  • DevSecOps for AI
  • Dubai Smart City
  • System design
  • Integration approach
  • Performance metrics

Technical Governance

  • Architecture Review Boards
  • Change Management Processes
  • Release Management
  • Configuration Management
  • Security Controls

Operational Controls 

  • Performance Monitoring
  • Capacity Planning
  • Disaster Recovery
  • Incident Management
  • SLA Management
  • Governance structure
  • Control framework
  • Risk management

Deployment Models

  • Continuous Integration/Deployment
  • A/B Testing Frameworks
  • Canary Deployments
  • Blue-Green Deployments
  • Shadow Deployments 

Quality Assurance

  • Testing Strategies
  • Performance Testing
  • Security Testing
  • Compliance Validation
  • User Acceptance Testing
  •  Etihad Airways
  • Deployment strategy
  • Testing approach
  • Quality metrics
  • Emerging Trends
  • Edge AI Architecture
  • Federated Learning Systems
  • Neural Architecture Search
  • AutoML Platforms
  • Quantum-Ready Architecture

Ready to Take the Next Step?

Reserve your slot today and start your learning journey with us.

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