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Track 05

Coming soon

AI Evaluation, Reliability & MLOps

Turn “it seems better” into evidence: evaluation sets, observability, versioning, and release gates that survive real traffic.

  • Intermediate
  • Chapters coming soon
See what's planned

What this track will cover

The outcomes the published chapters will build toward.

  1. Build an evaluation set that reflects production inputs
  2. Instrument a model feature so regressions are visible
  3. Set release gates for quality, latency, and cost

Main subjects

The territory this track covers.

  1. 01Evaluation frameworks
  2. 02Observability
  3. 03Versioning
  4. 04Deployment
  5. 05Regression gates
  6. 06Governance

Who this is for

Engineers responsible for shipping and operating AI features after the demo works.

Before you start

  • Basic statistics and sampling
  • Familiarity with CI/CD pipelines
  • Experience operating a production service

Curriculum

Chapters coming soon

In progress

Chapters are being written.

This track is scoped but not yet published. The subjects above are the planned path; lessons will appear here as each chapter is ready.

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