On-demand activities

Find the right on-demand learning activities for you. Labs are short learning activities that teach you a specific lesson by giving you direct, temporary, hands-on access to real cloud resources. Courses are longer activities, consisting of several modules made of videos, documents, hands-on labs and quizzes. Finally, quests are similar, but are usually shorter and contain only labs.

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111 results

  1. Course Featured

    BigQuery for Machine Learning

    Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and le…

  2. Lab Featured

    BigQuery Machine Learning using Soccer Data

    Learn how to use BigQuery ML with soccer shot data to create and use an expected goals model.

  3. Course Featured

    Production Machine Learning Systems

    This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed t…

  4. Lab Featured

    Machine Learning with TensorFlow in Vertex AI

    In this lab you will learn how to use Google Cloud Machine Learning and Tensorflow to develop and evaluate prediction models using machine learning.

  5. Course Featured

    Machine Learning in the Enterprise

    This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three…

  6. Course Featured

    Machine Learning Operations (MLOps): Getting Started

    This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professiona…

  7. Course Featured

    How Google Does Machine Learning

    This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a …

  8. Course Featured

    Managing Machine Learning Projects with Google Cloud

    Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine lear…

  9. Course Featured

    Applying Machine Learning to your Data with Google Cloud

    In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learnin…

  10. Lab Featured

    Fraud Detection on Financial Transactions with Machine Learning on Google Cloud

    Explore financial transactions data for fraud analysis, apply feature engineering and machine learning techniques to detect fraudulent activities using BigQuery ML.