ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML 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 ZenML.
These courses share topics with this one, so you can compare how each language or tool handles the same concept.
More in MLOps experiment management and deployment.
You have the curiosity.
Let’s turn it into capability.
Start with a practical workshop or bring a specific question to Ajay.