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AI IN DEVOPS

AI in DevOps is an 8-session professional course for DevOps, SRE, and Platform Engineers who want to move beyond AI autocomplete and use AI inside real infrastructure workflows.

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What is this course

A PRACTICAL UPGRADE

You already know DevOps.
Now learn how AI changes the way you work.

This is not a course about learning DevOps from scratch.
And it is not about MLOps or deploying machine-learning models.
It is about using AI for DevOps work — infrastructure, CI/CD, incident response, monitoring, remediation, documentation, security, and operational workflows.

  • 01

    Understand AI deeply

    Understand how LLMs, context, models, agents, and MCP work so you know where AI is reliable, where it fails, and what should never be delegated to it.

  • 02

    APPLY AI TO REAL WORK

    Use AI with Terraform, Kubernetes, CI/CD, logs, alerts, monitoring systems, runbooks, GitHub/GitLab, and real operational data.

  • 03

    Build WORKFLOWS

    This is the central promise of the course: the relevant skill is increasingly not simply prompting an LLM, but designing safe, controlled and traceable AI workflows around production systems.

Who is this for

BUILT FOR ENGINEERS WHO WANT TO WORK AI-NATIVE

  • DevOps Engineers

    Who already work with infrastructure and CI/CD and want to integrate AI into their everyday engineering workflows.

  • Site Reliability Engineers

    Who want to use AI to correlate alerts, logs, metrics and deployments and investigate incidents faster.

  • Platform Engineers

    Who want to build internal AI-enabled workflows and tools for engineering teams.

  • Cloud Engineers

    Who regularly work with infrastructure-as-code, Kubernetes, deployment systems and operational automation.

  • Infrastructure Engineers

    Who want AI to help review, diagnose, document and safely modify infrastructure.

  • DevOps / SRE Team Leads

    Who need to understand where AI automation is genuinely useful, where it introduces risk, and how to introduce AI safely inside their teams.

Curriculum

EIGHT SKILLS.
ONE MONTH.

  1. 01

    LLMs, Context & Prompting for Engineers

  2. 02

    AI CLI, Infrastructure Code & MCP

  3. 03

    AI for CI/CD, Code Review & Bug Fixing

  4. 04

    Build Your Own MCP Tool

  5. 05

    AIOps: From Alerts to Root Cause

  6. 06

    From Diagnosis to Action

  7. 07

    Safety, Security & Production Guardrails

  8. 08

    Capstone: Presentation & Wrap-up

Final Project

YOU DON'T GRADUATE WITH AN AI DEMO. YOU GRADUATE WITH A WORKING DEVOPS WORKFLOW.

Students select one of three capstone tracks.

Join the Bootcamp
  • 01

    AI Infrastructure Change with Gates

  • 02

    AI Incident Triage & Remediation Agent

  • 03

    AI Bug-Fix Loop

Start your journey at ACA X

Master AI skills.
Build your future.
Lead the change.

Course Fee: 100,000 AMD

Get up to 100,000 AMD back if you submit your annual tax declaration and have income tax.

Secure your spot now

Send your application. We will follow up with a short questionnaire and the technical requirements before payment.

About ACA

ACA X IS BACKED
BY 10 YEARS OF
TECH EDUCATION

ACAx is the professional AI direction of Armenian Code Academy - one of Armenia's most established tech education institutions, founded in 2015.

For a decade, ACA has trained engineers, designers, product managers, and data professionals who now work at global companies, local unicorns, and fast-growing startups. ACAx is the next evolution -professional AI skills for everyone, not just engineers.

  • 10+YEARS IN TECH EDUCATION
  • 17K+TOTAL GRADUATES
  • 100+PARTNER COMPANIES
  • 300+TUTORS

FREQUENTLY ASKED QUESTIONS

Who is this course designed for?
The course is designed primarily for DevOps Engineers, SREs, Platform Engineers, Cloud Engineers and Infrastructure Engineers who already work with Kubernetes, infrastructure as code, and a CI system.

Do I need prior knowledge of AI tools?
Basic familiarity with AI tools is helpful. This is not a beginner prompting course — it is an advanced practical program for technical professionals who want to apply AI across engineering workflows.
Is this course only about AI-assisted coding?
No. Coding is only part of it. The course covers infrastructure code (Terraform, Kubernetes), CI/CD and automated bug fixing, connecting AI to your real systems through MCP, incident diagnosis and alert noise, agents that take action with human approval, and the safety rules that make all of this usable in production.