MLOps 102 – Production-Ready ML Pipelines

John Enoh · November 30, 2025

(Weeks 3–4 | Lec 6 Hrs / Lab 18 Hrs / Ext 0 Hrs | 24 Total Hrs | 1.0 Credit Hrs)
Students will:

  • Automate end-to-end ML workflows
  • Build training, validation, and deployment pipelines
  • Handle data drift and schema evolution
  • Manage experiments systematically
    Prerequisite: MLOps 101 – ML Engineering Foundations
    Tools: Kubeflow Pipelines, MLflow, Metaflow

About Instructor

John Enoh

121 Courses

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Course Includes

  • 10 Lessons

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