Amazon SageMaker topics
12 short topics in AI Evaluation LLMOps and Governance. Each one is a single focused exercise with a clear piece of evidence at the end.
12 topics, one exercise each.
Work through them in order, or jump to the one you need.
These are draft topic outlines (draft; instructor review pending). Full lessons follow after review; ask Ajay if you need a topic sooner.
- 01
Experiment identity and metadata
Demonstrate experiment identity and metadata in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 02
Dataset and feature versioning
Demonstrate dataset and feature versioning in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 03
Model artifact tracking
Demonstrate model artifact tracking in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 04
Pipeline step organization
Demonstrate pipeline step organization in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 05
Training reproducibility
Demonstrate training reproducibility in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 06
Evaluation and promotion criteria
Demonstrate evaluation and promotion criteria in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 07
Serving deployment integration
Demonstrate serving deployment integration in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 08
Model resource configuration
Demonstrate model resource configuration in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 09
Runtime diagnostics
Demonstrate runtime diagnostics in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 10
Model update and rollback
Demonstrate model update and rollback in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 11
Access and provenance boundaries
Demonstrate access and provenance boundaries in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 12
MLOps integration testing
Demonstrate mlops integration testing in a focused Amazon SageMaker example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course →
Learn the same ideas beyond Amazon SageMaker.
These courses share topics with this one, so you can compare how each language or tool handles the same concept.
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