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AI Interview MasteryMid → SeniorNEW
LLMOps & Deployment
Deployment, monitoring, and scaling questions for production LLM roles. From containerising an AI API to monitoring latency and cost in Azure Monitor — the operational skills that separate ML engineers from AI platform engineers.
4.8rating1,410 students1h 20m total16 lessons
What you'll learn
Containerise an AI API with Docker and deploy to Azure Container Apps
Set up a CI/CD pipeline that tests, builds, and deploys an LLM service
Monitor LLM latency, token cost, and error rate with Azure Monitor
Implement structured logging with structlog for AI applications
Design rollback and blue-green deployment for LLM services
Answer any LLMOps interview question asked in senior AI roles
Final Project
Design and present the full deployment architecture for a production LLM service: CI/CD, monitoring, scaling, and rollback
Curriculum
16 lessons · 1h 20mCourse Info
Lessons16 lessons
Total time1h 20m
LevelMid → Senior
Students1,410
Rating4.8 / 5.0