AI-Powered DevOps: Intelligent Platform Engineering

Detailed Curriculum · 72 teaching hours · 56 traditional + 16 AI-augmented

Prerequisites: You don't need a computer science degree or years on the job — if you can write basic code in any backend language (C#, Java, Python, Go, and TypeScript all work fine), have poked around a cloud console before, and know your way around Git, you're ready to start. No prior AI or LLM experience needed — that's exactly what this course teaches you. 

Positioning:
In this course, DevOps and Platform Engineering are not treated as two separate areas of expertise, but as two complementary parts of a holistic engineering approach required to take software from commit to production and operate it reliably at scale.

The course covers the full spectrum of CI/CD pipelines and infrastructure, containers and service mesh, cloud operations, the platform-as-a-product approach and internal developer platforms, data governance, FinOps, and reliability at scale.

While each topic is covered in meaningful depth, the program brings them together into a single, focused 72-hour learning journey. Lab time, case-study scope, and optional advanced topics are structured and condensed to maintain a coherent and intensive learning experience.

The program concludes with a 16-hour AI-Augmented DevOps and Platform Engineering module, where participants explore through hands-on work where agentic AI and automation can genuinely create value across pipelines and platforms.