From AIOps monitoring and LLM-powered log analysis to KubeGPT and real-world AI-driven CI/CD pipelines — the next evolution of DevOps is here.
Most AI course outlines are a pile of tool names with no sense of when to use any of them. This one is sequenced the way the field is actually adopted on the job: you start by understanding what machine learning is and how it learns, then move outward into the places it genuinely pays off — watching noisy systems with AIOps, drafting infrastructure code, reading logs and forecasting cost with large language models, and debugging clusters with KubeGPT. Each module below opens to a short explanation of why it matters and what you will have built, not just the topics it lists.
The eight modules run from foundations through hands-on tooling and finish with five real-time projects you assemble yourself. If you are new to AI in operations, work top to bottom; if you already lean on Copilot or an observability platform, use the filters above to jump to AIOps, AI Analysis or Kubernetes AI. Everything is taught practically against live tools and pipelines, mirroring the way AI-assisted delivery is built in NareshIT's project labs in Hyderabad.