TensorFlow Extended Courses and Certifications

Orchestrating a TFX Pipeline with Airflow

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you'll learn to create your own machine learning pipelines using TensorFlow Extended (TFX) and Apache Airflow as the orchestrator.

• Coursera
• 1 hour 30 minutes
• Self-Paced
• Paid Course

TFX on Google Cloud Vertex Pipelines

In this lab you will develop, deploy, and run a TFX pipeline on Google Cloud Vertex Pipelines.

• Google Skills
• 1-2 hours
• Self-Paced
• Paid Course

Orchestrating a TFX Pipeline with Airflow

In this lab, you'll learn to create your own machine learning pipelines using TensorFlow Extended (TFX) and Apache Airflow as the orchestrator.

• Google Skills
• 1-2 hours
• Self-Paced
• Paid Course

A Complete Guide on TensorFlow 2.0 using Keras API

2007 ratings at Udemy

Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0

• Udemy
• 13 hours 6 minutes
• Self-Paced
• Paid Course

ML Pipelines on Google Cloud

Build production ML pipelines with TFX components and orchestration, add CI/CD and ML metadata, and run continuous training with Kubeflow, Cloud Composer, and MLflow.

• Google Skills
• 2 hours 15 minutes
• Self-Paced
• Free Certificate

Advanced ML: ML Infrastructure

Deploy and scale TensorFlow models on Google Cloud using Vertex AI Pipelines, Kubernetes, TF Serving, and canary releases.

• Google Skills
• 4 hours 45 minutes
• Self-Paced
• Paid Course

GOTO Conferences

From Experimentation to Products - The Production Machine Learning Journey

Learn how TFX pipeline architectures move machine learning systems from experimentation into production.

• YouTube
• 38 minutes
• Self-Paced
• Conference Talk

A Year of Democratizing ML With Kubernetes & Kubeflow

Explore Kubeflow 1.0's new features for democratizing machine learning on Kubernetes, including web-based UI, simplified setup, and sophisticated ML tooling for end-to-end solutions.

• YouTube
• 36 minutes
• Self-Paced
• Conference Talk

Deploying ML at Scale with Kubernetes and TFX

Learn to deploy machine learning models at scale using Kubernetes and TensorFlow Extended (TFX), enhancing your ability to manage and scale ML workflows efficiently.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

MLOps World: Machine Learning in Production

Production ML for Mission-Critical Applications

Explore rigorous approaches for deploying ML in production, addressing scalability, testability, and performance analysis. Learn about TensorFlow Extended for large-scale applications.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Bringing Structure Into an Unstructured World - Applying State-of-the-Art Machine Learning at Digits

Explore how Digits applies transformer models to extract structured information from unstructured financial data and deploys ML experiments in production using TensorFlow.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

ML Pipelines on Google Cloud en Español

Aprende a automatizar y reutilizar canalizaciones de aprendizaje automático entre TensorFlow, PyTorch, scikit-learn y XGBoost con herramientas de Google Cloud.

• Coursera
• 3 hours 48 minutes
• Self-Paced
• Paid Course

ML Pipelines on Google Cloud - 한국어

여러 머신러닝 프레임워크의 파이프라인을 자동화·재사용하고 TFX, Cloud Composer, MLflow로 지속적 학습과 전체 수명 주기를 관리합니다.

• Coursera
• 4 hours
• Self-Paced
• Paid Course

ML Pipelines on Google Cloud - Français

Apprenez à orchestrer, automatiser et gérer des pipelines de machine learning en production avec TFX, CI/CD, plusieurs frameworks, Cloud Composer et MLflow.

• Coursera
• 4 hours
• Self-Paced
• Paid Course

ML Pipelines on Google Cloud - 日本語版

Google Cloud 上で TFX、Kubeflow、Cloud Composer、MLflow を使い、機械学習パイプラインのオーケストレーションと継続的トレーニングを実現する方法を学ぶ。

• Coursera
• 4 hours 25 minutes
• Self-Paced
• Paid Course