AIOps Foundation – with PeopleCert Certification Exam

Course Agenda

Day 1 – Foundations of AIOps® and Intelligent IT Operations

Module 1. Introduction to AIOps® – Why the Future of IT Operations Has Already Begun

The course begins by exploring the evolution of AIOps®, the business challenges it addresses, and why leading organizations are increasingly adopting Artificial Intelligence to transform the way IT Operations are managed.

During this module, you will learn about:

  • The history and evolution of AIOps®
  • The differences between traditional IT Operations, ITOA, and AIOps®
  • The core technologies behind AIOps®: Artificial Intelligence, Machine Learning, and Big Data
  • How an AIOps platform works
  • The four key stages of an AIOps solution:
    • Data Ingestion
    • Insights
    • Collaboration
    • Remediation
  • How Artificial Intelligence supports analysis, prediction, and automation
  • Real-world AIOps® implementation examples from leading organizations
  • Interactive discussions and practical exercises

 

Module 2. AIOps® in the Modern Organization

Once the foundations are established, we explore why AIOps® is becoming a strategic capability for modern digital organizations.

Topics include:

  • Digital Transformation as the driving force behind AIOps
  • The evolution from monolithic applications to Cloud and Microservices
  • Monitoring versus Observability
  • Why operational data is growing exponentially
  • How AIOps supports DevOps practices
  • The role of AIOps in Site Reliability Engineering (SRE)
  • The relationship between AIOps and Cybersecurity
  • When an organization is ready to adopt AIOps®

Practical Exercise

Develop an Error Budget and explore how AIOps® contributes to achieving Service Reliability Objectives.

 

Module 3. Core Technologies – Data as the Foundation of AIOps®

Every successful AIOps platform begins with high-quality data.

In this module, participants will explore:

  • Operational data sources
  • Logs
  • Metrics
  • Events
  • Alerts
  • Traces
  • Telemetry
  • Data Pipelines
  • Data Quality
  • Data Aggregation
  • Data Correlation
  • Big Data Architecture
  • Why “Garbage In – Garbage Out” matters
  • Building reliable data pipelines for AI-driven operations

Practical Exercise

Designing a data collection and analysis workflow for an AIOps environment.

 

Module 4. Machine Learning as the Engine of AIOps®

With the right data in place, Artificial Intelligence can begin delivering meaningful operational insights.

Topics include:

  • Machine Learning fundamentals
  • Supervised Learning
  • Unsupervised Learning
  • Pattern Recognition
  • Anomaly Detection
  • Predictive Analytics
  • Root Cause Analysis
  • Event Correlation
  • How AI discovers relationships between operational events
  • How Machine Learning supports intelligent operational decision-making

Interactive Discussion

Where Artificial Intelligence enhances human expertise—and where experienced IT professionals remain essential.

 

Day 2 – Applying and Implementing AIOps®

 

Module 5. Measuring IT Operations Performance

You cannot improve what you do not measure.

This module focuses on the operational metrics that matter most.

Topics include:

  • Operational Metrics
  • Service Metrics
  • Business Metrics
  • MTTR
  • MTBF
  • Availability
  • Reliability
  • Error Rates
  • Service Health
  • SLI
  • SLO
  • SLA
  • How AIOps® improves operational performance and service quality

Practical Exercise

Selecting the right KPIs to measure the success of an AIOps initiative.

 

Module 6. Real-World AIOps Use Cases and Organizational Transformation

AIOps® is not simply another technology—it changes how organizations operate.

During this module, participants will explore:

  • Real-world implementation scenarios
  • Intelligent Incident Management
  • Predictive Maintenance
  • Intelligent Alerting
  • Root Cause Analysis
  • Self-Healing Systems
  • The evolving role of IT professionals in AI-enabled operations
  • Organizational culture and AIOps adoption
  • New competencies required for modern IT Operations teams

Interactive Discussion

How the role of IT engineers is evolving in the age of Artificial Intelligence.

 

Module 7. Measuring the Business Impact of AIOps®

Every technology investment should deliver measurable business value.

Topics include:

  • Return on Investment (ROI)
  • Business Value
  • Operational Efficiency
  • Customer Experience
  • Continual Improvement
  • Measuring outcomes after implementation
  • Demonstrating the business value of AIOps®

Practical Exercise

Building a framework for evaluating the success of an AIOps implementation.

 

Module 8. Successfully Implementing AIOps®

The final module brings together everything learned throughout the course into a practical implementation roadmap.

Topics include:

  • AIOps implementation strategy
  • Organizational readiness
  • Change Management
  • Selecting appropriate technologies
  • Risk Management
  • Industry best practices
  • Common implementation challenges
  • Critical success factors
  • Building an AIOps implementation roadmap

Practical Exercise

Developing a sample implementation plan for introducing AIOps® within an organization.

 

Certification Exam Preparation

Throughout the two-day course, participants receive:

  • Official PeopleCert® courseware
  • Interactive exercises and group discussions
  • Analysis of real-world business scenarios
  • Sample certification exam questions
  • Practical guidance and exam preparation tips
  • Comprehensive preparation for the PeopleCert® AIOps® Foundation certification exam

This two-day official accredited course follows the PeopleCert® AIOps® Foundation syllabus, combining internationally recognized best practices with practical examples and interactive learning to help participants confidently prepare for both the certification exam and real-world implementation.