AI & Machine Learning · Beginner → Expert
⚙️ MLOps and Machine Learning Platforms
Operationalize ML with data/version control, experiments, pipelines, model registries, deployment, monitoring, drift detection, governance and automation.
Course roadmap
Pass each module exam to unlock the next module.
Module 1 · Beginner
MLOps Lifecycle and Reproducibility
Locked
Module 2 · Beginner
Data Versioning and Dataset Management
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Module 3 · Beginner
Experiment Tracking and Model Metadata
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Module 4 · Beginner
Feature Pipelines and Feature Stores
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Module 5 · Intermediate
Training Pipelines and Orchestration
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Module 6 · Intermediate
Model Packaging and Registries
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Module 7 · Intermediate
Batch Inference and Online Serving
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Module 8 · Intermediate
Containers and Kubernetes for ML
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Module 9 · Advanced
CI/CD/CT for Machine Learning
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Module 10 · Advanced
Model Monitoring and Data Drift
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Module 11 · Advanced
Performance, Latency and Capacity Planning
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Module 12 · Advanced
Security, Privacy and Access Control
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Module 13 · Expert
Governance, Approval and Auditability
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Module 14 · Expert
Rollback, Shadow, Canary and A/B Deployment
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Module 15 · Expert
Cost Management and Platform Operations
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Module 16 · Expert
Expert Capstone: Governed ML Platform
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Certification gate
Final course exam
Pass mark: 80%. Time limit: 360 minutes. All module exams must be passed first.
Locked until modules are passed