// school · mlops-infrastructure
🚀MLOps & Infrastructure
Docker, Kubernetes, CI/CD, model serving, monitoring, and cloud deployment. The price of admission for enterprise AI.
Start This School// career outcomes
Where This School Takes You
// core skills
What You Will Master
// your path
Path Through This School
Phase 01
Foundation
Prove your fundamentals. Python, Git, SQL, APIs, Docker, and AI basics — calibrated to your level before you touch MLOps & Infrastructure.
Phase 02
Build
Work through real MLOps & Infrastructure tickets inside virtual companies. Ship features, fix bugs, and build systems under production constraints.
Phase 03
Prove
Every submission is scored across 5 dimensions. Build a verified Proof-of-Competency profile that proves you can do the work of a MLOps Engineer.
// your faculty
Your Faculty
Dr. Chen Wei
Dean
Production-obsessed. Nothing ships until it’s monitored, tested, and documented. Zero tolerance for "it works on my machine."
Viktor
Lead Instructor
Infrastructure veteran. Thinks in systems, not scripts. Will make you draw architecture diagrams before writing YAML.
Fatima
Inference optimization, cost management
Andrei
Observability, drift detection, alerting
Ready to start MLOps & Infrastructure?
Begin with Foundation. Prove your baseline. Then build real systems.
Start Building