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AI models don’t run themselves in production. This course teaches you the infrastructure skills to take models from a Jupyter notebook to a scalable containerized service. Covers Docker fundamentals, Kubernetes orchestration, GPU resource management, and deploying AI APIs at scale.

✅ What’s Inside:

  1. Why Containers for AI
  2. Docker Fundamentals
  3. Writing Efficient Dockerfiles
  4. Docker Compose for Development
  5. Kubernetes Architecture
  6. Deploying Your First Pod
  7. Services and Ingress
  8. Persistent Storage for Models
  9. GPU Node Configuration
  10. Horizontal Scaling Strategies
  11. Monitoring with Prometheus
  12. Project: Deploy a Model Serving API