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Sammy Cheung

成为会员时间：2021

白银联赛

2400 积分
Generative AI Fundamentals - 简体中文徽章 Generative AI Fundamentals - 简体中文 Earned Jul 18, 2023 EDT
Introduction to Responsible AI - 简体中文徽章 Introduction to Responsible AI - 简体中文 Earned Jul 18, 2023 EDT
Introduction to Large Language Models - 简体中文徽章 Introduction to Large Language Models - 简体中文 Earned Jul 18, 2023 EDT
Introduction to Generative AI - 简体中文徽章 Introduction to Generative AI - 简体中文 Earned May 18, 2023 EDT
Developing a Google SRE Culture徽章 Developing a Google SRE Culture Earned Mar 16, 2023 EDT
Google Workspace for IT Administrators徽章 Google Workspace for IT Administrators Earned Dec 27, 2022 EST
Planning for a Google Workspace Deployment徽章 Planning for a Google Workspace Deployment Earned Dec 25, 2022 EST
Google Workspace Mail Management徽章 Google Workspace Mail Management Earned Dec 25, 2022 EST
Google Workspace Security徽章 Google Workspace Security Earned Dec 25, 2022 EST
Managing Google Workspace徽章 Managing Google Workspace Earned Dec 24, 2022 EST
Introduction to Google Workspace Administration徽章 Introduction to Google Workspace Administration Earned Dec 24, 2022 EST
Gmail徽章 Gmail Earned Dec 24, 2022 EST
Production Machine Learning Systems徽章 Production Machine Learning Systems Earned Oct 15, 2022 EDT
Machine Learning in the Enterprise徽章 Machine Learning in the Enterprise Earned Oct 14, 2022 EDT
Feature Engineering徽章 Feature Engineering Earned Oct 13, 2022 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud徽章 Build, Train and Deploy ML Models with Keras on Google Cloud Earned Aug 24, 2022 EDT
How Google Does Machine Learning徽章 How Google Does Machine Learning Earned Aug 23, 2022 EDT
Launching into Machine Learning徽章 Launching into Machine Learning Earned Aug 23, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals徽章 Google Cloud Big Data and Machine Learning Fundamentals Earned Aug 20, 2022 EDT
Securing and Integrating Components of your Application徽章 Securing and Integrating Components of your Application Earned Jun 17, 2022 EDT
Scaling with Google Cloud Operations徽章 Scaling with Google Cloud Operations Earned Jun 15, 2022 EDT
Cloud Architecture - Design, Implement, and Manage徽章 Cloud Architecture - Design, Implement, and Manage Earned Jun 14, 2022 EDT
DEPRECATED Cloud Architecture徽章 DEPRECATED Cloud Architecture Earned Jun 9, 2022 EDT
Reliable Google Cloud Infrastructure: Design and Process - 简体中文徽章 Reliable Google Cloud Infrastructure: Design and Process - 简体中文 Earned Jun 7, 2022 EDT
Preparing for your Professional Cloud Architect Journey徽章 Preparing for your Professional Cloud Architect Journey Earned Jun 4, 2022 EDT
Cloud Engineering徽章 Cloud Engineering Earned Jun 3, 2022 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation - 简体中文徽章 Elastic Google Cloud Infrastructure: Scaling and Automation - 简体中文 Earned Jun 1, 2022 EDT
Google Cloud Essentials徽章 Google Cloud Essentials Earned Jun 1, 2022 EDT
Essential Google Cloud Infrastructure: Core Services - 简体中文徽章 Essential Google Cloud Infrastructure: Core Services - 简体中文 Earned May 31, 2022 EDT
Essential Google Cloud Infrastructure: Foundation - 简体中文徽章 Essential Google Cloud Infrastructure: Foundation - 简体中文 Earned May 28, 2022 EDT
Google Cloud Fundamentals: Core Infrastructure - 简体中文徽章 Google Cloud Fundamentals: Core Infrastructure - 简体中文 Earned May 26, 2022 EDT
Google Cloud Fundamentals for AWS Professionals徽章 Google Cloud Fundamentals for AWS Professionals Earned May 26, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey 徽章 Preparing for Your Associate Cloud Engineer Journey Earned May 25, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud徽章 Modernize Infrastructure and Applications with Google Cloud Earned Mar 28, 2022 EDT
Exploring Data Transformation with Google Cloud徽章 Exploring Data Transformation with Google Cloud Earned Mar 14, 2022 EDT
Digital Transformation with Google Cloud徽章 Digital Transformation with Google Cloud Earned Mar 14, 2022 EDT

完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程，赢取技能徽章。通过最终测验，即表明您理解了生成式 AI 的基本概念。 技能徽章是由 Google Cloud 颁发的数字徽章，旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中，以此来分享您获得的成就。

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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。

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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

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这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.

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In this quest, you will gain hands-on experience on several topics in Google Workspace Administration including security, provisioning users and groups, managing applications, and managing Google Meet.

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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Google Workspace Mail Management is the fourth course in the Google Workspace Administration series. In this course you will learn how to protect your organization against spam, spoofing, phishing and malware attacks. You will configure email compliance and learn how to implement data loss prevention (DLP) for your organization. You will gain an understanding of the mail routing options available and learn how to allowlist and block senders. You will also become familiar with other mail options such as inbound and outbound gateways, 3rd party email archiving, and journaling to Vault.

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Google Workspace Security is the third course in the Google Workspace Administration series. In this course you will focus on the various aspects of Google Workspace Security including user password policies and how to enable and enforce two step verification (2SV) for your users. You will learn about application security and understand how to whitelist and block API access to your account. You will see how Google Workspace can easily be integrated with a number of predefined 3rd party applications. You will also become familiar with the SSO options in Google Workspace. Finally you will understand how to spot potential security risks within your organization and learn how to address them using the tools available in the admin console.

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Managing Google Workspace is the second course in the Google Workspace Administration series. This course focuses on the Google Workspace core services such as Gmail, Calendar, and Drive & Docs. You will become familiar with the various service settings, and learn how to enable them for all or just a subset of your users. You will gain an understanding of Google Vault, Google’s ediscovery service. You will understand the various admin console reports that are available and be able to search and filter the information in these reports. Finally you will see how multiple domains can be used with Google Workspace and learn how to add a new domain to your account.

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Introduction to Google Workspace Administration is the first course in the Google Workspace Administration series of courses. This series will serve as the starting place for any new Google Workspace admin as they begin their journey of managing and establishing Google Workspace best practices for their organization. These courses together will leave you feeling confident to utilize the basic functions of the admin console to manage users, control access to services, configure security settings, and much more. Through a series of readings and step-by-step hands-on exercises, and knowledge checks, learners can expect to leave this training with all of the skills they need to get started as Google Workspace administrators. In this course you will sign up for a Google Workspace account and configure your DNS records for Google Workspace. You will learn how to provision and manage your users, and will create groups and calendar resources for your organization. You will be introduced to …

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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser. In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels. You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates. Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.

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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 training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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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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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.

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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.

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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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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.

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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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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to develop more secure applications, implement federated identity management, and integrate application components by using messaging, event-driven processing, and API gateways. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer. This is the second course of the Developing Applications with Google Cloud series. After completing this course, enroll in the App Deployment, Debugging, and Performance course.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using Google Cloud architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many Google Cloud technologies. All labs have activity tracking, and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your Google Cloud technology skills to the test! Be aware that while practice with these labs will increase your knowledge and abilities, additional study, experience, and background in cloud architecture is recommended to prepare for this certification. Complete this quest to receive an exclusive Google Cloud digital badge.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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本课程指导学员运用久经考验的设计模式在 Google Cloud 上构建高度可靠且高效的解决方案。它是“Google Compute Engine 架构设计”或“Google Kubernetes Engine 架构设计”课程的延续，并假定您有使用其中任何一门课程所涵盖技术的实践经验。通过一系列演示、设计活动和动手实验，学员可以了解如何定义及平衡业务要求和技术要求，以便设计可靠性和可用性高、安全且经济实惠的 Google Cloud 部署。

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This course helps learners create a study plan for the PCA (Professional Cloud Architect) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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这是一套自助式速成课程，向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务。学员将通过一系列视频讲座、演示和实操实验，探索和部署各种解决方案元素，包括安全互连网络、负载均衡、自动扩缩、基础架构自动化和代管式服务。

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在此入门级挑战任务中，您可以使用 Google Cloud Platform 的基本工具和服务，开展真枪实弹的操作实训。“GCP 基本功能”是我们为 Google Cloud 学员推荐的第一项挑战任务。云知识储备微乎其微甚至零基础？不用担心！这项挑战任务会为您提供真枪实弹的实操经验，助您快速上手 GCP 项目。无论是要编写 Cloud Shell 命令还是部署您的第一台虚拟机，亦或是通过负载平衡机制或在 Kubernetes Engine 上运行应用，都可以通过“GCP 基本功能”了解该平台的基本功能之精要。点此观看 1 分钟视频，了解每个实验涉及的主要概念。

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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务，着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验，探索和部署各种解决方案元素，包括网络、系统和应用服务等基础架构组件。本课程的内容还包括如何部署实用的解决方案，包括客户提供的加密密钥、安全和访问权限管理、配额和结算，以及资源监控。

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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务，其中着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验，探索和部署各种解决方案元素，包括网络、虚拟机和应用服务等基础架构组件。您将学习如何通过控制台和 Cloud Shell 使用 Google Cloud。您还将了解云架构师角色、基础架构设计方法以及虚拟网络配置和虚拟私有云 (VPC)、项目、网络、子网、IP 地址、路由及防火墙规则。

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“Google Cloud 基础知识：核心基础架构”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务，并提供重要的资源和政策管理工具。

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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. 'Modernize Infrastructure and Applications with Google Cloud' explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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