Overview
Intelligent Service Operations focuses on transforming traditional IT operations into adaptive, automated, and predictive service environments using Artificial Intelligence (AI), Machine Learning (ML), analytics, and operational automation. The objective is to improve service reliability, operational efficiency, responsiveness, and user experience through intelligent decision-making and autonomous operational capabilities.
This module introduces modern approaches to operating IT services using real-time monitoring, event intelligence, predictive analytics, automated remediation, and AI-assisted operational workflows. Learners will understand how intelligent operations reduce manual intervention, accelerate issue resolution, and support continuous service improvement.
Participants will explore operational models that integrate AI capabilities into monitoring, incident response, performance optimization, capacity planning, and operational governance to build resilient and scalable digital services.
- IT Operations professionals
- Service Operations managers
- Site Reliability Engineers (SRE)
- Infrastructure and platform engineers
- Network and cloud operations teams
- Service delivery managers
- IT support and operations analysts
- DevOps professionals
- Automation and AIOps practitioners
- Digital operations and transformation leaders
Recommended Prior Knowledge
- Basic understanding of IT operations and service delivery
- Familiarity with service management concepts
- Foundational knowledge of automation and analytics
- Awareness of cloud and modern infrastructure environments
1. Foundations of Intelligent Service Operations
- Evolution from traditional operations to AI-native operations
- Principles of intelligent and autonomous operations
- Operational efficiency and service value creation
- Business alignment and service outcomes
2. Monitoring and Operational Visibility
- Real-time infrastructure and application monitoring
- Unified observability practices
- Metrics, logs, traces, and event management
- Operational dashboards and service health indicators
3. Event Intelligence and Incident Response
- AI-driven event correlation
- Noise reduction and alert prioritization
- Predictive incident identification
- Intelligent escalation and routing mechanisms
4. Automation and Autonomous Operations
- Workflow automation and orchestration
- Automated remediation and self-healing systems
- Runbook automation
- Human-in-the-loop operational models
5. Predictive and Proactive Operations
- Predictive maintenance concepts
- Capacity and demand forecasting
- Performance optimization strategies
- Risk anticipation and prevention
6. Operational Analytics and Decision Support
- Service intelligence and operational analytics
- Root cause analysis using AI
- Data-driven operational decisions
- Continuous operational optimization
7. Governance, Security, and Reliability
- Operational governance principles
- Reliability engineering practices
- Compliance and operational controls
- Responsible AI in operational environments
8. Emerging Intelligent Operations Trends
- AIOps adoption models
- Generative AI in operations
- Autonomous operations platforms
- Future of intelligent service ecosystems
- Multiple Choice Questions (MCQ)
- Scenario-based problem solving
- Case-study evaluation
- Operational decision-making exercises
- Minimum score: 65%
- Certification validity: As defined by the certification authority
- Recommended study duration: 12–16 hours
Policies
Training Options
Corporate Training
We work with customers to provide tailor made training solutions, onsite and off site delivery with customized content to cover areas of key importance. Please contact for private batches or any other requirements.