DevOps Engineering with AI
Modern platform teams are small and expected to move fast. We train engineers who codify everything, automate the rest, and let AI handle the toil.
- Duration
- 22 weeks
- Format
- Live online + on-demand labs
- Commitment
- 15–20 hrs/week (part-time track available)
- Level
- Beginner to job-ready
- Tuition
- TBD
- Next cohort
- January 12, 2027
The shape of the program.
Build a production-grade platform on AWS with Terraform, Kubernetes, and GitOps.
Wire AI into your pipelines: code review, test generation, incident summaries, runbooks.
Graduate with a public repo that any hiring manager can clone and run.
By graduation you can
- Provision reproducible cloud infrastructure with Terraform modules
- Run containerised workloads on Kubernetes with autoscaling and rollbacks
- Design CI/CD pipelines with progressive delivery and automated gates
- Instrument systems for observability: metrics, logs, traces, SLOs
- Use AI agents for on-call triage, cost analysis, and remediation PRs
Tools & platforms
- AWS
- Terraform
- Docker
- Kubernetes
- Helm
- ArgoCD
- GitHub Actions
- Prometheus
- Grafana
- OpenTelemetry
- Ansible
- Python
Certifications you will be ready for
- AWS Solutions Architect Associate
- Certified Kubernetes Administrator (CKA)
- HashiCorp Terraform Associate
Roles graduates target
- DevOps EngineerTBD
- Platform EngineerTBD
- Site Reliability EngineerTBD
- Cloud Infrastructure EngineerTBD
Roles our graduates target. Compensation data is not published here and no particular outcome is guaranteed.
22 weeks, four phases, one portfolio.
Each phase ends with a graded lab reviewed by an instructor. Nothing is auto-marked.
Weeks 1–4
Linux, Git & Cloud Foundations
- Linux administration, shell scripting, and systemd
- Git workflows, trunk-based development, and code review
- AWS core services: VPC, EC2, IAM, S3, RDS
- Networking and DNS for engineers
Weeks 5–10
Infrastructure as Code & Containers
- Terraform modules, state management, and drift control
- Docker images, multi-stage builds, and registry hygiene
- Kubernetes workloads, services, ingress, and storage
- Helm, Kustomize, and environment promotion
Weeks 11–17
CI/CD, GitOps & Reliability
- GitHub Actions pipelines with reusable workflows
- ArgoCD and GitOps deployment patterns
- Prometheus, Grafana, OpenTelemetry, and SLO design
- Chaos testing, incident review, and postmortems
Weeks 18–22
AI Operations & Platform Engineering
- LLM-assisted code review and test generation in CI
- AI on-call copilots: alert summarisation and runbook execution
- FinOps: automated cost anomaly detection and rightsizing
- Capstone: multi-environment platform with full GitOps delivery
Not quite the right fit?
Advisors regularly steer applicants toward a different track. Nobody benefits from you being in the wrong one.
Ready to start DevOps Engineering with AI?
The next cohort begins January 12, 2027. Applications take about ten minutes and there is no fee.
Tuition: TBD — pricing information available upon request at admissions@aiskool.us