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Go from first principles to running a production ML platform: data versioning, feature stores, CI/CD/CT, Kubernetes serving, monitoring, drift detection, security, cost, LLMOps, and incident response.

Deploy, scale and manage containerized applications with Kubernetes in production.

The complete hands-on Docker course — 22 real terminal labs covering CLI, registries, Dockerfiles, networking, Compose, security, cleanup, production hardening, and a final interview exam. Built like KodeKloud.

Learn to deploy, scale, and troubleshoot applications on Kubernetes.

Design and lead risk-based testing from requirements through release sign-off.

Containerize any application and master Docker for modern development workflows.

Build networking knowledge from packets and CIDR to DNS, HTTP, routing, firewalls, and incident diagnosis.

Go from your first shell command to safely operating, troubleshooting, and automating a Linux server.

Connect quality work to product discovery, delivery, operations, and risk.

Make quality signals fast, reproducible, observable, and enforceable in delivery pipelines.