TensorFlow Extended (TFX) Training Course


TensorFlow Extended (TFX) is an end-to-end platform for deploying production ML pipelines.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to go from training a single ML model to deploying many ML models to production.

By the end of this training, participants will be able to:

  • Install and configure TFX and supporting third-party tools.
  • Use TFX to create and manage a complete ML production pipeline.
  • Work with TFX components to carry out modeling, training, serving inference, and managing deployments.
  • Deploy machine learning features to web applications, mobile applications, IoT devices and more.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.


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


  • Data scientists
  • ML engineers
  • Operation engineers

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

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