Machine learning and Artificial intelligence
Did you know that the adoption of machine learning results in 2x more data-driven decisions, 5x faster decision-making, and 3x faster execution?
Learn how to implement the latest machine learning and artificial intelligence technology by exploring training on BigQuery, Datalab, TensorFlow, Cloud Vision, Natural Language API, and more.

Get started with Google Cloud's big data and machine learning products like BigQuery, Cloud SQL, Dataproc, and more. In this introductory course, you'll learn how to best process data and create ML models for your needs.
Get started with big data, machine learning, and artificial intelligence. Take your first steps with Google Cloud tools like BigQuery, Cloud Speech API, and AI Platform. You'll have the opportunity to earn a Google Cloud skill badge upon completion.
In this course you will experiment with end-to-end machine learning on Google Cloud, starting from building a machine learning-focused strategy and progressing into model training, optimization, and productionalization.
Interactions with Contact Center AI should be conversational and human-like. Learn how to build a virtual agent, design conversational flows for your virtual agent, and add a phone gateway to a virtual agent.
This advanced course teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text, and ends with building recommendation systems. This content can also be taken as part of the Advanced Solutions Lab.
Get hands-on practice with Explainable AI - a set of tools and frameworks to help you develop interpretable and inclusive machine learning models and deploy them with confidence. Complete this quest, including the challenge lab at the end, to receive an exclusive Google Cloud digital badge.
In this course you will learn MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. This content can also be taken as part of the Advanced Solutions Lab.
In this course you will learn how to implement ML pipelines with continuous training and CI/CD practices to increase your ML workflow development and deployment velocity, automation, and ability to scale with your data on Google Cloud. This content can also be taken as part of the Advanced Solutions Lab.
Related Information
What you learn
TensorFlow, AI Platform Notebooks, Cloud Dataflow, Cloud DataFusion, AI Platform, BigQuery, BigQuery ML, Cloud ML APIs, Kubeflow Pipelines