AIOps 基金會℠
港幣 9,900.00
Certified AIOps Foundation℠
持續時間：2天
Language: English/ Cantonese/Putonghua
遠距現場講師指導的互動式認證培訓
額外資訊
| 工作家庭 | AI, DevOps SRE |
|---|---|
| 角色 | AIOps Architects, AIOps Engineers, Business Manager, Cloud Engineers, Data Engineers, Data Scientists, DevOps engineers, DevOps Practitioners, IT Directors, IT Managers, IT Operation, IT Security Analysts, Product Owners, Scrum Masters, Site Reliability Engineers, Software Engineers, System Integrators |
| 能力水平 | 基礎 |
| 工作坊類別 | AI |
工作坊描述
This course 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. It is tailored for those focused on understanding basic concepts, implementations, use cases, and benefits.
This AIOps FoundationSM course covers the origins of AIOps, including the history behind the
term, patterns that preceded it, and the technological context in which it has evolved. Learners
will gain an understanding of the processes of combining Big Data analytics, Machine Learning
algorithms, Generative AI, 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 provides learners with an
understanding of how and why digital transformation, together with the evolution of Machine
Learning and Generative AI, have brought about the rise of AIOps as an indispensable tool in
today’s IT Operational landscape.
Core technologies of Big Data, Machine Learning and Generative AI are discussed, as well as the
basic concepts of artificial intelligence, different types of Machine Learning models that can be
implemented, the relationship between AIOps and MLOps, as well as DevOps and Site Reliability.
This foundation course provides the learner 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.
Practical, real-world exercises are 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 FoundationSM certification
exam.
Why Choose AIOps?
Stay Ahead of Evolving Technologies
The AIOps Foundation certification will equip you with the necessary knowledge to navigate the complexities of cloud-native applications and harness artificial intelligence for IT Operations.
Master Cutting-edge Technologies
Gain an in-depth understanding of how artificial intelligence, big data analytics and machine learning can be combined to optimise IT processes.
Drive Digital Transformation Efforts
Explore the synergy between digital transformation, machine learning, and the rise of AIOps to spearhead initiatives that seamlessly integrate AIOps into organisational workflows.
Overcome Common Challenges, Maximise Benefits
Acquire the tools and practical strategies needed to overcome common hurdles and maximise the benefits of AIOps adoption. Gain a greater understanding of deployment effectiveness and learn to quantify outcomes using industry-standard metrics.
觀眾
- 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
Course objectives
The learning objectives for the AIOps FoundationSM course include a practical understanding
of:
• the basic concepts, industry contexts, and key principles of AIOps
• the concepts and principles of core technologies required for AIOps implementation
• the changes in organizational mindset and required skill sets for deploying AIOps
• how to evaluate the performance of an AIOps implementation using industry standard metrics
• the challenges and opportunities that arise when looking to deploy AIOps in the organization
• key considerations and strategies required to succeed in promoting and delivering AIOps in your organization.
What will you learn?
AIOps Fundamentals
Discover how AIOps has evolved through the years, the difference between AIOps and IT Operations Analytics, and the current stages of an AIOps system.
AIOps in the Organization
Learn how AIOps can be integrated into organizational frameworks, and its impact on DevOps, site reliability, security, and system complexity.
Core Technologies: Big Data
Gain an introduction to Big Data, covering what Big Data is, the Five V’s, its key characteristics, AIOps data sources/types, and diverse data.
Core Technologies: Machine Learning (ML)
Explore AI and Machine Learning in AIOps, supervised vs. unsupervised learning, ML vs. analytics, training models, and future prospects.
AIOps and Operations Metrics
Leverage industry standard metrics to quantify the outcomes of implementing AIOps.
AIOps Use Cases and Organizational Mindset
Understand the challenges and opportunities of applying AIOps in the organization.
Evaluating AIOps Impact
Measure the effectiveness of AIOps deployment and its potential benefits.
Implementing AIOps
Discover the challenges, trends and ethical considerations organizations may face while deploying an AIOps initiative.
Course outline
介紹
Module 1: AIOps Foundation
• History and predecessors
• Core technologies and basic concepts
• AIOps capability chain
Module 2: AIOps in the organization
• Drivers and influences
• AIOps and DevOps
• AIOps and Site Reliability Engineering
• AIOps and security
Module 3: Core technologies: Data
• What is Big Data?
• Five Vs of Big Data
• AIOps data sources and types
• From source to AIOps
Module 4: Core Technologies: Machine Learning (ML) and Generative AI (GenAI)
• AI, ML, and GenAI
• How ML models learn
• Supervised versus unsupervised
• Analytics versus AI
• AIOps and the future of AI
Module 5: AIOPs and operations metrics
• Metrics and operations
• Key metrics to track across systems
• Agreements, objectives and indicators
Module 6: AIOps use cases and organizational mindset
• Shifting from reactive to proactive
• Deterministic to probabilistic
• Deep dive into use cases
Module 7: Evaluating AIOps’ impact
• AIOps and operations metrics
• AIOps, DevOps, and SRE
• Improving AI accuracy
• AIOps system visibility
Module 8: Implementing AIOps in the organization
• Avoiding common challenges
• Ethics and ML
先決條件
建議熟悉 IT 術語並具備 IT 相關工作經驗。
專業發展單位 (PDU)
專業發展單位 (PDU)
- 與會者可能有資格向專案管理協會 (PMI) 申請 14 個 PDU，以滿足其繼續教育要求，獲得 PMP®、PgMP® 和 PMI-ACP® 認證。
認證考試
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 the DevOps Institute, a member of the PeopleCert Group.
學習資料
- 2 天的講師指導訓練和運動輔導
- 學習手冊（優秀的課後參考）
- 參與旨在應用概念的獨特練習
- 範例文件、範本、工具和技術
- 獲得額外的增值資源和社區。
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繁體中文 
English (UK) 
简体中文 