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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 Machine Learning Engineer designs, builds, productionizes, optimizes, operates, and maintains ML systems.

Course

Big Data & Machine Learning Fundamentals

This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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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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Course

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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Course

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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Course

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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Course

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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Create Conversational AI Agents with Dialogflow CX

Learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features.

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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

    Courses

    5

  • Labs

    Labs

    27

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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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Resources

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