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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?1

Learn how to implement the latest machine learning and artificial intelligence technology by exploring training on BigQuery, TensorFlow, Cloud Vision, Natural Language API, and more.

Data Scientist / Machine Learning Engineer learning path

A Data Scientist models and analyzes key data to continually improve how businesses utilize data. Data Scientists aim to make accurate predictions about the future using in-depth data modeling and deep learning.

Learning path diagram for Data Scientist / Machine Learning Engineer


Big Data & Machine Learning Fundamentals

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.

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Perform Foundational Data, ML, and AI Tasks in Google Cloud

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.

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Machine Learning on Google Cloud

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.

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Advanced Machine Learning with TensorFlow on Google Cloud Platform

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.

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Explore ML models with Explainable AI

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.

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MLOps (Machine Learning Operations) Fundamentals

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.

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ML Pipelines on Google Cloud

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.

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Build and Deploy Machine Learning Solutions on Vertex AI

Get practice with Vertex AI platform, AutoML, and custom training services. You'll learn how to use Vertex AI for new and existing ML workloads, as well as how to leverage AutoML, custom training, and new MLOps services to significantly enhance development productivity and accelerate time to value.

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  • Products

    What you'll learn

    TensorFlow, AI Platform Notebooks, Cloud Dataflow, Cloud DataFusion, AI Platform, BigQuery, BigQuery ML, Cloud ML APIs, Kubeflow Pipelines

  • Courses



  • Labs



Take the next step

Additional courses and practice

Advanced Solutions Lab

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The Advanced Solutions Lab is a 4-week, full-time immersive training program in applied machine learning. It provides a unique opportunity for your technical teams to dive into a particular machine learning use case for your business. Attendees learn alongside Google's machine learning experts in a dedicated, collaborative space on Google Campus.

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Digital events and webinars


Ready to get started?

Enroll today and claim your exclusive Google Cloud training discounts.

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