AIOps Engineer Training Course

5 days of intensive, hands-on training to build production-grade AIOps pipelines and automation workflows.

Course Overview

Build Real-World AIOps Systems

The AIOps Engineer Training Course is an intensive 5-day, 40-hour program designed for hands-on practitioners who need to design, build, and maintain AIOps data pipelines and automation workflows. Unlike the foundation course, this training is deeply technical, with over 60% of the time spent in lab environments working with real tools and datasets.

You will gain practical experience with the AIOps toolchain, building data ingestion pipelines that handle millions of events per minute, implementing anomaly detection algorithms on live metric streams, and creating auto-remediation runbooks that respond to incidents in seconds. Each module culminates in a hands-on lab that reinforces the concepts with production-realistic scenarios.

The course concludes with a full-day capstone project where you build an end-to-end AIOps solution from data ingestion through automated remediation. This training directly prepares you for the Certified AIOps Engineer exam, with the voucher included in your enrollment.

Quick Facts

  • Duration: 5 Days / 40 Hours
  • Format: Live Virtual or In-Person
  • Labs: Dedicated cloud lab environment
  • Level: Intermediate to Advanced
  • Certification: Certified AIOps Engineer
  • Price: $1,499 (includes exam voucher)
Learning Outcomes

What You'll Learn

Practical engineering skills you will master during this training.

AIOps Toolchain Mastery

Gain hands-on proficiency with leading AIOps platforms, open-source tools, and integration frameworks used in production environments.

Data Pipeline Engineering

Design and implement high-throughput data ingestion pipelines that collect, normalize, and enrich metrics, logs, and traces at scale.

Anomaly Detection Implementation

Implement statistical and ML-based anomaly detection on live data streams using real algorithms and production-grade configurations.

Auto-Remediation Workflows

Build automated incident response workflows with proper escalation paths, safety guardrails, and rollback mechanisms.

CI/CD Integration

Integrate AIOps monitoring and feedback loops into CI/CD pipelines for deployment verification, canary analysis, and automated rollbacks.

End-to-End Solution Design

Architect and build a complete AIOps solution from data collection through intelligent alerting and automated response in the capstone project.

Target Audience

Who Should Attend

This hands-on course is built for engineers who implement and operate AIOps systems.

  • DevOps Engineers building observability and automation pipelines
  • Site Reliability Engineers (SREs) implementing intelligent monitoring
  • Platform Engineers designing internal tooling with AI capabilities
  • Infrastructure Engineers automating operations at scale
  • Monitoring Engineers transitioning to AI-driven observability
  • Automation Engineers expanding into ML-powered runbooks
  • Data Engineers working with operational telemetry data
  • AIOps Foundation certified professionals ready for the next level
Course Details

Training Details

Duration

5 Days / 40 Hours
8 hours per day

Format

Live Virtual Classroom
or In-Person

Lab Environment

Dedicated cloud labs
with pre-configured tools

Hands-On Ratio

60% labs & exercises
40% instruction

Curriculum

Course Curriculum

A structured 5-day deep dive into AIOps engineering practices.

Module 1: AIOps Toolchain Deep Dive
  • Evaluating and selecting AIOps platforms
  • Open-source vs. commercial tool comparison
  • Prometheus, Grafana, and Elasticsearch stack deep dive
  • Agent-based vs. agentless data collection
  • Lab: Setting up a complete monitoring stack
Module 2: Data Pipeline Engineering
  • Designing high-throughput data ingestion architectures
  • Stream processing with Apache Kafka and Flink
  • Log parsing, normalization, and enrichment pipelines
  • Metric aggregation and downsampling strategies
  • Lab: Building a multi-source data pipeline
Module 3: Anomaly Detection Implementation
  • Implementing statistical anomaly detection (Z-score, MAD, IQR)
  • ML-based detection with isolation forests and autoencoders
  • Dynamic baseline computation for seasonal patterns
  • Tuning detection sensitivity and reducing false positives
  • Lab: Deploying anomaly detection on live metrics
Module 4: Auto-Remediation Workflows
  • Designing remediation workflows and decision trees
  • Building runbooks with Ansible, Terraform, and custom scripts
  • Implementing safety guardrails and blast radius controls
  • Escalation paths and human-in-the-loop patterns
  • Lab: Creating an auto-scaling remediation workflow
Module 5: CI/CD Integration
  • Integrating AIOps into deployment pipelines
  • Canary analysis and automated deployment verification
  • ML-based change risk scoring for releases
  • Automated rollback triggers and feature flag integration
  • Lab: Building a deployment verification pipeline
Module 6: Capstone Project
  • Design and build an end-to-end AIOps solution
  • Integrate data pipeline, detection, and remediation
  • Present and defend your architecture decisions
  • Peer review and instructor feedback session
  • Exam preparation workshop and practice test
Certification Prep

Prepare for the Certified AIOps Engineer Exam

This training course covers all domains of the Certified AIOps Engineer exam. The hands-on labs give you the practical experience needed to tackle the performance-based exam questions, and the capstone project mirrors the exam's scenario-based format.

  • Exam voucher included with course enrollment
  • Performance-based and multiple-choice exam format
  • 90-minute exam with 50 questions and 2 lab scenarios
  • Prerequisite: AIOps Foundation Certification recommended
View Certification Details

Certified AIOps Engineer

Validates your ability to design, build, and operate AIOps data pipelines and automation systems in production environments.

50
Questions
90
Minutes
70%
Pass Score
Pricing

Pricing & Registration

Comprehensive hands-on training with everything you need to succeed.

AIOps Engineer Training

$1,499

Per participant — all-inclusive package

  • 5 days of live instructor-led training
  • Dedicated cloud-based lab environment
  • Official AIOps Engineer courseware and lab guides
  • Certified AIOps Engineer exam voucher
  • Capstone project review and feedback
  • 60-day post-training lab access and mentor support
Enroll Now

Group discounts available for 5+ participants

FAQs

Frequently Asked Questions

While the AIOps Foundation certification is recommended, it is not a strict prerequisite. You should have a solid understanding of IT operations, basic scripting skills (Python or Bash), and familiarity with monitoring tools like Prometheus, Nagios, or Datadog.

The lab environment includes Prometheus, Grafana, Elasticsearch, Kibana, Apache Kafka, Ansible, Terraform, and custom Python-based ML pipelines. All tools are pre-configured in your cloud lab, so no local installation is required.

You receive lab access from the first day of training and it continues for 60 days after course completion. This gives you ample time to revisit exercises, experiment with configurations, and prepare for the certification exam.

On the final day, you design and build an end-to-end AIOps solution that includes a data ingestion pipeline, anomaly detection, and automated remediation. You will present your solution to the class and receive feedback from the instructor and peers.

Yes, we offer private corporate training sessions that can be customized with your organization's tools, datasets, and use cases. Contact us for a custom quote and tailored agenda that addresses your team's specific needs.

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