成为会员时间：2020
Build a Certification Study Guide: PMLE
Earned Nov 20, 2025 EST
Analyzing and Visualizing Data in Looker
Earned Jul 10, 2024 EDT
基准：数据、机器学习和 AI
Earned Sep 20, 2020 EDT
在 Google Cloud 中使用 Kubernetes
Earned Sep 1, 2020 EDT
Machine Learning APIs
Earned Aug 19, 2020 EDT
Data Catalog Fundamentals
Earned Aug 15, 2020 EDT
DEPRECATED BigQuery for Marketing Analysts
Earned Aug 13, 2020 EDT
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
大数据、机器学习和人工智能是当今计算领域的热门话题， 但这些领域的专业性很强，因而很难找到 入门资料。幸运的是，Google Cloud 在这些领域提供了方便用户使用的服务， 通过本入门级课程，您可以 开始学习使用 BigQuery、Cloud Speech API 和 Video Intelligence 等工具。
Kubernetes 是最受欢迎的容器编排系统， Google Kubernetes Engine 专为支持 Google Cloud 中的托管式 Kubernetes 部署 而设计。在本高级课程中，您将亲自动手配置 Docker 映像、容器，并部署功能完备的 Kubernetes Engine 应用。 此课程将帮助您掌握在工作流中集成容器编排所需的 实用技能。 想要参加实操实验室挑战赛， 展示您的技能并检验所学知识？完成本课程后，不妨继续参与这项额外的 实验室挑战赛，赢得 Google Cloud 专属数字徽章。 该挑战赛位于在 Google Cloud 上部署 Kubernetes 应用课程的结尾处。
It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.