按照您自己的方式探索 Google Cloud 培训。

Google Cloud 提供 980 多项学习活动供您选择,我们设计的目录完整全面,充分考虑了您的需求。该目录包含各种可供您选择的活动形式,既有简短的单个实验,也有由视频、文档、实验和测验组成的多模块课程,您可以根据需求进行选择。我们的实验可为您提供实际云资源的临时凭据,以便您通过实际操作掌握 Google Cloud 知识。您可以跟踪、衡量和了解自己的 Google Cloud 学习进度,完成学习活动即可赢取徽章!

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1214 条结果
  1. 实验 精选

    Generative AI: Sprinting Tour

    Arcade chatbot lab to learn about the sprinting at the Olympics

  2. 实验 精选

    Generative AI: Swimming Tour

    Arcade chatbot lab to learn about the swimming events at the Olympics

  3. 实验 精选

    Getting Started with MongoDB Atlas on Google Cloud

    In this lab you will provision a MongoDB Atlas database and deploy a MEAN Cloud Run app

  4. 实验 精选

    Getting Started with Vertex AI Gemini 1.5 Flash

    This lab will provide an introductory, hands-on experience with Generative AI on Google Cloud.

  5. 实验 精选

    Grounding Gemini Models in Vertex AI

    In this lab, you will learn how to use grounding in Vertex AI to generate content grounded in your own documents and data.

  6. 实验 精选

    Introduction to Controlled Generation with the Gemini API

    In this lab, you will learn how to use the controlled generation capability in the Vertex AI Gemini API.

  7. 实验 精选

    Introduction to Vertex AI Embeddings: Text and Multimodal

    In this lab, you will explore the Vertex AI Embeddings API for both Text and Multimodal (Images and Video) use cases.

  8. 实验 精选

    Migrating an application and data from Apache Cassandra™ to DataStax Enterprise

    In this lab, you will learn how to migrate an application running on Apache Cassandra™ to DataStax Enterprise (DSE). To do this, you will deploy a Cassandra™ database and an application that writes data into it. You will then deploy a DataStax Enterprise database and connect the same application to the database. F…

  9. 实验 精选

    Multimodal Use Cases with Gemini 1.5

    In this lab, you will learn how to use Gemini 1.5 Pro and Gemini 1.5 Flash LLMs for multimodal use cases.

  10. 实验 精选

    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.