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在 Google Cloud 控制台中运用您的技能

Tran Tuyet Hue

成为会员时间：2022

白银联赛

6200 积分
How Google Does Machine Learning Earned Nov 14, 2022 EST
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs Earned Nov 14, 2022 EST
Deprecated Kubernetes Solutions Earned Oct 8, 2022 EDT
DEPRECATED Applied Data: Blockchain Earned Oct 8, 2022 EDT
Machine Learning in the Enterprise Earned Oct 7, 2022 EDT
在 Google Cloud 中使用 Kubernetes Earned Oct 5, 2022 EDT
DEPRECATED Anthos Service Mesh Earned Oct 3, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Oct 3, 2022 EDT
用 Google Data Cloud 共享数据 Earned Oct 3, 2022 EDT
使用 BigQuery 构建数据仓库 Earned Sep 20, 2022 EDT
Analyzing and Visualizing Data in Looker Earned Sep 20, 2022 EDT
Creating New BigQuery Datasets and Visualizing Insights Earned Sep 20, 2022 EDT
用　Database Migration Service　将 MySQL 数据迁移至 Cloud SQL Earned Sep 16, 2022 EDT
从 BigQuery 数据中挖掘数据洞见 Earned Sep 14, 2022 EDT
在 Vertex AI 上构建和部署机器学习解决方案 Earned Sep 14, 2022 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Sep 14, 2022 EDT

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 candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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In this quest you will use a collection of Google APIs that are all related to language, and speech. You will use the Speech-to-Text API to transcribe an audio file into a text file, the Cloud Translation API to translate from one language to another, the Cloud Translation API to detect what language is being used and translate to a different language, the Natural Language API to classify text and analyze sentiment, and create synthetic speech.

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Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.

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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.

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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 options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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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。

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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on Google Cloud. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.

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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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完成用 Google Data Cloud 共享数据技能徽章课程，赢取技能 徽章。您将获得使用 Google Cloud 数据共享合作伙伴 的实操经验，这些合作伙伴拥有专有数据集， 客户可将其用于自己的分析应用场景。客户订阅这些数据集，可在自己的 平台上查询，然后使用自己的数据集加以扩充，并使用自己的可视化 工具，用于面向客户的信息中心。

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完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。

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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.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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完成用　Database Migration Service　将 MySQL 数据迁移至 Cloud SQL 这一入门级的技能徽章课程，展示您在以下方面的技能： 使用 Database Migration Service 中提供的不同作业类型和连接选项，将 MySQL 数据迁移到 Cloud SQL； 以及在运行 Database Migration Service 作业时 迁移 MySQL 用户数据。

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完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Looker Studio 中 创建报告。

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完成在 Vertex AI 上构建和部署机器学习解决方案课程，赢取中级技能徽章。 在此课程中，您将了解如何使用 Google Cloud 的 Vertex AI Platform、AutoML 以及自定义训练服务来 训练、评估、调优、解释和部署机器学习模型。 此技能徽章课程的目标受众是专业的数据科学家和机器学习 工程师。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程 和作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。

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完成中级技能徽章课程利用 BigQuery ML 构建预测模型时的数据工程处理， 展示自己在以下方面的技能：利用 Dataprep by Trifacta 构建 BigQuery 数据转换流水线； 利用 Cloud Storage、Dataflow 和 BigQuery 构建提取、转换和加载 (ETL) 工作流； 以及利用 BigQuery ML 构建机器学习模型。

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