The AIOps Foundation course provides a thorough introduction to the origins and evolution of AIOps, exploring the historical context, emerging patterns, and technological advancements that have shaped its development. Participants will learn how AIOps integrates big data analytics, machine learning, automation, and optimization into a unified approach to modern IT operations.
The course covers essential principles and foundational concepts, with a focus on the core technologies of AIOps—big data and machine learning. Learners will understand the impact of digital transformation and how advancements in machine learning have made AIOps a vital component of today’s IT infrastructure.
Topics include an overview of artificial intelligence, various machine learning models, and how AIOps relates to MLOps, DevOps, and Site Reliability Engineering. The course also explores the benefits of implementing AIOps, common challenges faced during adoption, and key steps for successful integration within an organization.
Interactive exercises, practical examples, templates, and tools are included to help students apply their knowledge beyond the classroom. By completing this course, learners will be equipped to take the AIOps Foundation certification exam and support AIOps initiatives in their workplace.
Target Audience:
The AIOps Foundation course is designed for a broad range of professionals involved in IT operations and digital transformation. It is ideal for individuals who are looking to understand and apply AIOps concepts in modern IT environments. This includes:
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IT Operations professionals
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Individuals interested in the evolving IT software landscape
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AIOps Architects and Engineers
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Business Managers and Key Stakeholders
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Cloud Engineers
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Data Engineers and Data Scientists
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DevOps Engineers and Practitioners
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IT Directors and IT Managers
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IT Security Analysts
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Team Leaders within IT departments
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Product Owners and Scrum Masters
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Software Engineers
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Site Reliability Engineers (SREs)
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System Integrators
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Providers of AIOps platforms and tools
Course Objectives:
At the end of the course, the following learning objectives are expected to be achieved:
- Clear understanding of the history, origins and current developments of AIOps
- Define and comprehend basic concepts and key principles within AIOps
- Understand general concepts of big data and artificial intelligence, and how they relate to AIOps
- Recognize the relationship between AIOps and MLOps
- Understand the effectiveness of AIOps deployment and possible benefits
- Understand the changes in mindset, collaboration and skills for AIOps to be applied in the organization
- Quantify outcomes of an AIOps implementation leveraging industry standard metrics
- Understand usual challenges and opportunities of applying AIOps in the organization
- Visualize the challenges, trends and ethical considerations organizations might face while deploying an AIOps initiative
Course Content
Course Introduction
An overview of the course structure, objectives, and learning outcomes.
Module 1: AIOps Foundation
Explore the origins, definitions, and core principles of AIOps, including the historical and technological context that led to its emergence.
Module 2: AIOps in the Organization
Understand the role of AIOps in modern IT organizations and how it supports digital transformation and operational efficiency.
Module 3: Core Technologies – Data
Dive into big data concepts, sources of operational data, and how data collection and processing support AIOps solutions.
Module 4: Core Technologies – Machine Learning (ML)
Learn the fundamentals of machine learning, types of ML models, and their applications in AIOps environments.
Module 5: AIOps and Operations Metrics
Examine how AIOps leverages metrics and KPIs to drive intelligent decision-making and optimize IT performance.
Module 6: AIOps Use Cases and Organizational Mindset
Review real-world AIOps use cases and understand the cultural shift required for successful AIOps adoption.
Module 7: Evaluating AIOps Impact
Explore methods for assessing the effectiveness and business value of AIOps initiatives within the organization.
Module 8: Implementing AIOps in the Organization
Identify best practices, common challenges, and key steps for integrating AIOps tools and strategies into existing IT operations.
Course Prerequisites:
Participants are recommended to have a basic understanding of IT terminology and some prior experience in IT-related roles. While no advanced technical knowledge is required, familiarity with IT operations, systems, or infrastructure will enhance the learning experience.
Certification Exam
To earn the AIOps Foundation certification, candidates must pass a 60-minute exam consisting of 40 multiple-choice questions. A passing score of 65% is required.
This certification is governed and maintained by the DevOps Institute, part of the PeopleCert Group, ensuring global recognition and professional credibility.
