MLOps 103 – Containerization & Model Serving

(Weeks 5–6 | Lec 6 Hrs / Lab 18 Hrs / Ext 0 Hrs | 24 Total Hrs | 1.0 Credit Hrs)
Students will:

• Containerize ML models using Docker
• Deploy models to production with FastAPI and TensorFlow Serving
• Design scalable model serving architectures
• Integrate model endpoints with APIs
  Prerequisite: MLOps 102 – Production-Ready ML Pipelines
  Tools: Docker, Kubernetes, TensorFlow Serving