MLOps & Model Serving
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10 lessons3 levels1 capstone project
Productionize ML with experiment tracking, reproducible training, data/model versioning, registries, batch/online serving, CI/CD/CT, feature pipelines, monitoring, drift, rollback, governance, and cost/performance optimization.
BASIC
- What Is MLOps? — IBM Technology (8 min)
Clear bridge from model development to automated, reliable production operations. - MLOps Zoomcamp — DataTalksClub (25 min selected)
Maps the full ML lifecycle: design, train, deploy, operate, monitor. - Practical Deep Learning Lesson 1 Hands-On Video — fast.ai (20 min selected Time)
Refresh the iterative train/evaluate loop that MLOps operationalizes. Build / Practice
INTERMEDIATE
- Data Platform for the AI Frontier — Microsoft Fabric
Apply MLOps & Model Serving through the adjacent capability: Data Platform. - Architecture & Key Concepts — Snowflake
Apply MLOps & Model Serving through the adjacent capability: Data Platform. - Data Governance Explained — IBM Technology
Apply MLOps & Model Serving through the adjacent capability: Data Quality, Governance & Lineage.
ADVANCED
- Quality, Lineage, Privacy and Trust — Data Governance
Extend MLOps & Model Serving into senior/production practice through Data Quality, Governance & Lineage. - Airflow, Databricks, Kubernetes — Build a Data Platform from Scratch
Extend MLOps & Model Serving into senior/production practice through Data Pipelines, Orchestration & Streaming. - Key Building Block for Governance — Data Lineage
Extend MLOps & Model Serving into senior/production practice through Data Quality, Governance & Lineage.