AIOps Fundamentals Training in Kuala Lumpur

AIOps Fundamentals Training in Kuala Lumpur, Malaysia

Participants will explore how AI and machine learning enhance IT operations by reducing noise, identifying patterns, and proactively addressing incidents.

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AIOps Fundamentals Training is a professional training program delivered by ProgNXT in Kuala Lumpur, Malaysia. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this AIOps Fundamentals Training course with hands-on, instructor-led sessions. This course provides foundational knowledge in AIOps, focusing on monitoring, event correlation, and intelligent alerting....

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: LLM80
14 Hrs
Last Updated: April 2026

Course Rating5/5

This course provides foundational knowledge in AIOps, focusing on monitoring, event correlation, and intelligent alerting. Participants will explore how AI and machine learning enhance IT operations by reducing noise, identifying patterns, and proactively addressing incidents. The course includes both conceptual understanding and practical implementation techniques.

Welcome to the official AIOps Fundamentals Training certification program in Kuala Lumpur, Malaysia. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic understanding of IT operations and infrastructure
Familiarity with monitoring tools (e.g., Nagios, Zabbix, Prometheus)
General awareness of DevOps or ITSM workflows
No prior AI/ML experience required

By the end of the course, participants will be able to design and implement foundational AIOps practices in IT operations. They will know how to leverage monitoring data, correlate events, and deliver smart alerting that improves reliability and reduces operational overhead.

Understand the principles of AIOps and its architecture
Design monitoring strategies enhanced by AI
Correlate events from multiple sources using AIOps platforms
Implement intelligent alerting with reduced noise and high precision
Evaluate AIOps tools and use cases for enterprise environments

Core concepts of AIOps and its value in modern IT
AI-powered monitoring and anomaly detection
Event noise reduction and correlation techniques
Designing actionable and context-aware alerting
Integration with incident response and automation tools

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

Foundations of AIOps and Intelligent Monitoring

Introduction to AIOps

Definition and scope of AIOps
AIOps in the context of ITOM, DevOps, and SRE
Key components: monitoring, analytics, automation, and collaboration
Benefits: faster incident response, cost reduction, improved uptime

Monitoring Evolution and AIOps Integration

Traditional monitoring vs AI-enhanced monitoring
Metrics, logs, traces, and topology as data sources
Role of data volume, velocity, and variety in AIOps
Real-world examples of intelligent monitoring in use

Anomaly Detection and Pattern Recognition

Types of anomalies: point, contextual, collective
Statistical vs machine learning approaches
Use of baselines and dynamic thresholds
Benefits of real-time anomaly detection

Event Correlation and Intelligent Alerting

Event Correlation in AIOps

Importance of correlation in noisy environments
Event storms, duplicate alerts, and false positives
Topology-aware and time-series correlation
Rule-based vs AI-driven correlation engines

Designing Intelligent Alerting Systems

Characteristics of intelligent alerts: relevance, accuracy, context
Alert enrichment with metadata, logs, and incident history
Suppression, deduplication, and escalation logic
Integrating with ticketing, incident response, and chatops tools

Tooling Landscape and Architecture Design

Overview of AIOps platforms
Building blocks of an AIOps pipeline
Data ingestion, model training, feedback loops
Choosing the right architecture for your organization

Final Use Case Walkthrough and Assessment

Design a basic AIOps monitoring and alerting architecture
Walk through a correlated alert scenario from detection to resolution
Identify improvement areas using intelligent feedback
Review questions and recap of key takeaways

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on:
Daily quizzes, mock questions and query resolution. Participation in hands-on exercises and labs. Performance in the final review and hands-on exercises will be evaluated.
ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

AIOps Fundamentals Training Events in kuala-lumpur

Online Events

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More Upcoming Session Dates

October 2026

🌐 Online Instructor-Led

26th Oct 2026→27th Oct 2026

November 2026

🌐 Online Instructor-Led

2nd Nov 2026→3rd Nov 2026

📍 Kuala Lumpur, Malaysia

8th Nov 2026→9th Nov 2026

📍 Kuala Lumpur, Malaysia

20th Nov 2026→21st Nov 2026

🌐 Online Instructor-Led

27th Nov 2026→28th Nov 2026

December 2026

📍 Kuala Lumpur, Malaysia

5th Dec 2026→6th Dec 2026

🌐 Online Instructor-Led

11th Dec 2026→12th Dec 2026

📍 Kuala Lumpur, Malaysia

21st Dec 2026→22nd Dec 2026

🌐 Online Instructor-Led

21st Dec 2026→22nd Dec 2026

Events for other courses in Kuala Lumpur, Malaysia

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AIOps Fundamentals Training in Kuala Lumpur