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AIOps Foundation

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DURATION: 16 Hours

Introduces the history, background, technologies, organizational challenges and strategies towards
applying artificial intelligence for IT Operations, or AIOps, a rapidly growing industry driven by the rapidly
evolving IT operational environments of cloud native applications. Tailored for those focused on
understanding basic concepts, implementations, use cases and benefits.
 
This AIOps Foundation course aims to cover the origins of AIOps including the history behind the term,
patterns that preceded it and the technology context in which it has evolved. Learners will gain an
understanding of the processes of combining big data analytics, machine learning algorithms, automation,
and optimization into a single platform.
 
This course introduces key principles and foundational concepts along with the core technologies of
AIOps: big data and machine learning. The course will provide students with an understanding of how and
why digital transformation, together with the evolution of machine learning, have brought about the rise
of AIOps as an indispensable tool in today’s IT Operational landscape.
 
Core technologies of machine learning and big data will be discussed, as well as the basic concepts of
artificial intelligence, different types of machine learning models that can be implemented, and the
relationship between AIOps and MLOps, DevOps and Site Reliability.
 
This foundation course will also provide the student with a solid understanding of the benefits of
implementing AIOps in the organization, including common challenges and key steps in ensuring valuable
and successful integration of artificial intelligence in the day-to-day operations of information technology
solutions.
 
Unique and exciting exercises will be used to apply the concepts covered in the course and sample
Documents, templates, tools, and techniques will be provided to use after the class. This course positions
learners to successfully complete the AIOps Foundation certification exam.

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.

Audience:

  • Anyone focused on IT Operations.
  • Anyone interested in software in today’s IT landscape.
  • AIOps Architects and Engineers.
  • Business Managers, Stakeholders.
  • Cloud Engineers.
  • Data Engineers and Scientists.
  • DevOps Engineers and Practitioners.
  • IT Directors.
  • IT Managers.
  • IT Security Analysts.
  • IT Team Leaders.
  • Product Owners.
  • Scrum Masters.
  • Software Engineers.
  • Site Reliability Engineers.
  • System Integrators.
  • AIOps Platform and Tool Providers.

Learner Materials:

  • Sixteen (16) hours of instructor-led training and discussion facilitation.
  • Participation in unique exercises designed to apply concepts.
  • Sample documents, templates, tools and techniques.
  • Sample exam.
  • Glossary.
  • Access to additional value-added resources and communities.
Familiarity with IT terminology and IT related work experience are recommended.

Certification examcertification exam:
Successfully passing (65%) the 60-minute examination, consisting of 40 multiple-choice questions, leads
to the AIOps Foundation certificate. The certification is governed and maintained by DevOps Institute, a
member of the PeopleCert Group.
 
Course outline:

 

  • Module 1: AIOps Foundation.
  • Module 2: AIOps in the Organization.
  • Module 3: Core Technologies: Data.
  • Module 4: Core Technologies: Machine Learning (ML).
  • Module 5: AIOPs and Operations Metrics.
  • Module 6: AIOps Use Cases and Organizational Mindset.
  • Module 7: Evaluating AIOps Impact.
  • Module 8: Implementing AIOps in the Organization.
  • Get 10% discount on a group of 4 or more nominations! (Discount will be applied during checkout)
    Only applicable for selected batches and courses.

    AIOps Foundation

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