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MLOpsIntermediateNEW
MLflow — Experiment Tracking & MLOps
Bring software engineering discipline to machine learning — track experiments, compare runs, version models, and serve predictions via REST API. Covers Azure ML and Databricks integration.
4.8rating890 students3h 30m total1 lessons
What you'll learn
Track parameters, metrics, and artifacts for every training run
Compare runs to find the best-performing model
Register and version models with lifecycle stages (Staging → Production)
Serve models as REST APIs and in Docker containers
Integrate MLflow with Azure ML and Databricks
Final Project
Train, track, and deploy a churn prediction model with full MLflow lifecycle management
Curriculum
1 lessons · 3h 30mCourse Info
Lessons1 lessons
Total time3h 30m
LevelIntermediate
Students890
Rating4.8 / 5.0