CI/CD for ML

ML pipelines as code, testing, promotion gates and GitHub Actions.

8 concepts5 labs1 projects2 challenges

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Concepts

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CI/CD for ML

Concept · Hands-on lab included

CI for ML

Concept · Hands-on lab included

CD for ML

Concept · Hands-on lab included

GitHub Actions for ML

Concept · Hands-on lab included

Pipeline Gates and Approvals

Concept · Hands-on lab included

ML Pipeline Templating

Concept · Hands-on lab included

Artifact Versioning in CI/CD

Concept · Hands-on lab included

CI/CD for LLMs

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

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Build a Fast ML CI Check

35 min · intermediate · CI for ML

Promote a Model Through Stages

35 min · intermediate · CD for ML

Wire an ML CI Workflow

40 min · intermediate · GitHub Actions for ML

Parameterize a Template

35 min · advanced · ML Pipeline Templating

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Projects

Ship real projects and grow a portfolio that gets you interviews.

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advanced

Model Assurance CI/CD Pipeline

Every PR trains, tests and gates a candidate model

20 hrs

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Next modules

Keep your learning streak going with related modules.

ML Lifecycle

The full ML lifecycle and the operational discipline MLOps adds.

Experiment Tracking

MLflow tracking, run metadata, reproducibility and comparing experiments.

Dataset Versioning

DVC, data lineage and immutability for training data.