An Interactive 5-Day Training Course
AI Systems Architecture and Governance
Course Overview
This GLOMACS training course is designed for technical leaders responsible for shaping the future of enterprise AI systems. As organizations navigate the rapidly evolving technological landscape, developing scalable, robust, and well-governed AI architectures is essential for long-term success.
This five-day intensive AI Systems Architecture and Governance training course provides comprehensive knowledge and practical tools for designing, implementing, and governing enterprise-grade AI systems. Participants will gain insights from real-world AI implementations, mastering the complexities of modern AI architectures, cloud-native frameworks, and governance models.
Key Learning Outcomes:
- Comprehensive understanding of enterprise AI architecture patterns.
- Hands-on experience with AI system design and implementation.
- Real-world case studies from leading organizations in AI development.
- Strategic approaches to AI governance and risk management for enterprise systems
Training Objectives
By the End of This AI Systems Architecture and Governance Training Course, You Will Be Able To:
- Gain a thorough understanding of AI regulatory frameworks across different global regions.
- Implement adaptive governance strategies to ensure compliance in AI systems.
- Develop practical expertise in AI risk assessment and regulatory adherence.
- Design and establish governance frameworks tailored to organizational AI initiatives.
- Utilize real-world case studies to address AI-related challenges and enhance decision-making.
Who should Attend?
This GLOMACS training course is suitable for a wide range of professionals who are involved in AI, governance, risk management, compliance, and infrastructure architecture within their organizations. The course content is designed to benefit participants from various industries, including oil and gas, financial services, manufacturing, and telecommunications, among others.
This AI Systems Architecture and Governance training course is suitable to a wide range of professionals but will greatly benefit:
- Technical Program Managers leading AI initiatives
- DevOps Leaders managing AI infrastructure
- Cloud Architects designing AI solutions
- Infrastructure Managers overseeing AI systems
- Security Architects handling AI security
- MLOps Engineers managing AI pipelines
- AI Platform Engineers developing infrastructure
- Technical Project Directors implementing AI systems
About Saudi Glomacs
At Saudi GLOMACS, we specialize in delivering world-class training courses in Saudi Arabia and across various international locations. Our training courses are tailored to meet the unique demands of Saudi Vision 2030 and the Human Capability Development Program, focusing on empowering Saudi citizens and enhancing workforce skills. We offer diverse courses spanning leadership, management, engineering, and technical disciplines to cultivate expertise and drive professional growth. Our flexible learning options—whether in-person, online, or in-house—ensure accessibility and convenience for individuals and organizations alike.
With over 30+ years of experience through the GLOMACS global network, we are committed to delivering innovative, results-driven training solutions. Our expert instructors combine industry knowledge with dynamic teaching methods, fostering practical skill development and long-term career success. By choosing Saudi GLOMACS, you're investing in personal excellence and contributing to the Kingdom’s sustainable economic growth and vision-driven transformation.
Training Outline
DAY 1: DAY 1: AI Systems Foundation
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
DAY 2: DAY 2: AI System Components
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
DAY 3: DAY 3: Governance Framework
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
DAY 4: DAY 4: Implementation Strategies
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
DAY 5: DAY 5: Future Architecture
- Emerging Trends
- Edge AI Architecture
- Federated Learning Systems
- Neural Architecture Search
- AutoML Platforms
- Quantum-Ready Architecture
Providers and Associations
Sessions in international locations
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