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MLOps Professional
Advanced
4.8 (1.2k reviews)
Move models from notebooks to production. CI/CD for Machine Learning, Docker, and Kubernetes.
Best Seller
Course Roadmap
Step 1
Production ML Overview
The MLOps Lifecycle and Technical Debt
Step 2
Model Tracking
Experiment Tracking with MLflow and Weights & Biases
Step 3
Containerization
Docker Basics and Best Practices for ML Images
Step 4
Orchestration
Kubernetes (K8s) for Scaling Model Serving
Step 5
CI/CD Pipelines
GitHub Actions for Automated Testing and Deployment
Step 6
Model Serving
Flask, FastAPI, and TorchServe
Step 7
Monitoring & Drift
Detecting Data Drift and Concept Drift in Production
Step 8
Project
End-to-End Deployment of a Credit Risk Model