AIOps Foundation - accredited training with exam
training code: ZP-AIOpsF-DOIen / ENG DL 2d / ENAIOps Foundation 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.
This certification addresses key principles and foundational concepts along with the core technologies of AIOps: big data and machine learning. AIOps Foundation will validate candidates’ 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.
THE AIM OF A TRAINING PROJECT:
- 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.
The target audience for the AIOps Foundation course are professionals including:
- 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
Benefits for Individuals
- A clear understanding of the history, origins, and current developments of AIOps
- Defining and comprehend basic concepts and key principles within AIOps
- Understanding general concepts of big data and artificial intelligence and how they relate to AIOps
- Recognizing the relationship between AIOps and MLOps
- Understanding the effectiveness of AIOps deployment and possible benefits
Benefits for Organizations
- Understanding the changes in mindset, collaboration, and skills for AIOps to be applied in the organization
- Quantifying outcomes of an AIOps implementation leveraging industry-standard metrics
- Understanding the usual challenges and opportunities of applying AIOps in the organization
- Visualizing the challenges, trends, and ethical considerations organizations might face while deploying an AIOps initiative
The participants receive vouchers, which are valid for 6 months, for online exam.
Having completed the training, the participant receives an e-mail with guidelines how to register on the exam. The date is determined directly with PeopleCert, with the use of participant’s account.
Online exam is conducted in the presence of proctor – a person from PeopleCert, who connects remotely with training participant’s desktop and observes the course of exam via Internet camera.
The person who takes the exam is obliged to show the place where he is going to write the exam to proctor via Internet camera. Proctor checks if there are not any other persons and study aids in the room.
AIOps Foundation exam:
- exam duration 60 minutes
- 40 multiple-choice questions
- Required 65%, 26 correct answers
- Opened book
Familiarity with IT terminology and IT related work experience are recommended.
- Training: English
- Materials: English
- Exam: English
- Access to a platform with accredited training materials
- Voucher for the AIOps Foundation online exam
Additional options:
- Take2 re-sit exam: 200 zł
Attention: purchasing this option is only possible through Altkom Academy before the training.
- Module 1: AIOps Foundation
- History and Predecessors
- Meaning of AIOps
- Differences between AIOps and IT Operations Analytics
- Core Technologies and Basic Concepts
- Stages of an AIOps System
- Overlapping Practices
- Module 2: AIOps in the Organization
- Drivers and Influences
- AIOps and DevOps
- AIOps and Site Reliability
- AIOps and Security
- Data, Telemetry and Systems Complexity
- A New Paradigm to Understand System State
- Module 3: Core Technologies: Data
- What is Big Data?
- The Five V’s of Big Data
- Characteristics of Big Data
- AIOps Data Sources and Types
- Diverse Data
- Module 4: Core Technologies: Machine Learning (ML)
- AI and Machine Learning
- Supervised vs Unsupervised
- Machine Learning vs Analytics
- Machine Learning and Training Models
- AIOps and the Future of AI
- AIOps vs. Analytics Similarities and Differences
- Module 5: AIOPs and Operations Metrics
- Metrics and Operations
- Key Metrics to Track Across Systems
- Agreements, Objectives and Indicators
- Incident Related Metrics
- Quantifying Incidents (MTTD, MTBF, MTTA, MTTR)
- Service Level Agreements
- Module 6: AIOps Use Cases and Organizational Mindset
- Shifting from Reactive to Proactive
- Characteristics of a Reactive Approach to Operations
- Deterministic to Probabilistic
- Deep Dive Into Use Cases
- AIOps and Shifts in the Organization
- Understanding the Past and Predicting the Future
- Module 7: Evaluating AIOps Impact
- AIOps and Operations Metrics
- AIOps, DevOps and SRE
- Improving AI Accuracy
- AIOps System Visibility
- Tracking Impact of AIOps
- Impact to Incident Related Metrics
- AIOps and DORA Metrics
- Module 8: Implementing AIOps in the Organization
- Avoiding Common Challenges
- Ethics and Machine Learning
- Paths to Implementation
- Data Quality and Processes
- Culture and Organizational Practices
- Data and Regulation
- Machine Learning Bias
- Privacy and User Data