Course Outline


Setting up TensorFlow Extended (TFX)

Overview of TFX Features and Architecture

Understanding Pipelines and Components

Working with TFX Components

Ingesting Data

Validating Data

Tranforming a Data Set

Analyzing a Model

Feature Engineering

Training a Model

Orchestrating a TFX Pipeline

Managing Meta Data for ML Pipelines

Model Versioning with TensorFlow Serving

Deploying a Model to Production


Summary and Conclusion


  • An understanding of DevOps concepts
  • Machine learning development experience
  • Python programming experience


  • Data scientists
  • ML engineers
  • Operation engineers
  21 Hours


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