Firmansyah Wicaksono
成为会员时间:2023
青铜联赛
38285 积分
成为会员时间:2023
完成Google Cloud 云计算基础知识挑战任务,赢取技能徽章。 您将学习如何在 Compute Engine 中使用虚拟机 (VM)、永久性 磁盘和 Web 服务器。
This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
完成中级技能徽章课程使用 Vertex AI 中的 Gemini API 探索生成式 AI,展示自己在以下方面的技能: 文本生成技能、用于增强内容创作能力的图像和视频分析技能,以及在 Gemini API 中应用函数调用技术的技能。 了解如何运用先进的 Gemini 技术、探索多模态内容生成方法,并扩展 AI 赋能项目的功能。
完成中级技能徽章课程使用多模态 Gemini 和多模态 RAG 检查富文档,展示您在以下方面的技能: 将多模态与 Gemini 配合使用,从而使用多模态提示从文本数据和视觉数据中提取信息、生成视频说明、 检索视频中不包含的额外信息; 将多模态检索增强生成 (RAG) 与 Gemini 配合使用,以构建包含文本和图片的文档的元数据、获取所有相关文本块并输出引用。
In this course, you will learn about the various services Google Cloud offers for modernizing retail applications and infrastructure. Through a series of lecture content and hands-on labs, you will gain practical experience deploying cutting-edge retail and ecommerce solutions on Google Cloud.
本课程展示了如何在 BigQuery 中使用 AI/机器学习模型处理生成式 AI 任务。通过一个涉及客户关系管理的实际应用场景,您将学习到使用 Gemini 模型解决业务问题的工作流程。为了便于理解,本课程还将通过使用 SQL 查询和 Python 笔记本的编码解决方案提供分步指导。
This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
Complete the introductory Secure BigLake Data skill badge course to demonstrate skills with IAM, BigQuery, BigLake, and Data Catalog within Dataplex to create and secure BigLake tables.
Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.
Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.
Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.
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。
Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
完成 Cloud Speech API:3 种使用方式课程,赢取入门级技能徽章。 在本课程中,您将了解如何使用语音相关 API 工具来合成和转写语音。
完成“使用 Gemini 和 Imagen 构建实际 AI 应用”技能徽章入门课程,展示您在以下方面的技能:图像识别、自然语言处理、 使用 Google 强大的 Gemini 和 Imagen 模型生成图像、在 Vertex AI 平台上部署应用。
完成 在 Vertex AI 中设计提示入门技能徽章课程,展示以下方面的技能: Vertex AI 中的提示工程、图片分析和多模态生成式技术。探索如何编写有效的提示,指导生成式 AI 输出, 以及将 Gemini 模型应用于真实的营销场景。
完成入门级使用 Google Cloud Observability 进行监控和记录技能徽章课程, 展示自己在以下方面的技能:监控 Compute Engine 中的虚拟机; 利用 Cloud Monitoring 监控多个项目;将监控和日志记录功能扩展到 Cloud Functions; 创建和发送自定义应用指标;以及根据自定义指标配置 Cloud Monitoring 提醒。
Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.
Welcome to the second part of the two part course, Observability in Google Cloud. This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
In this course, you will learn the basic skills to implement secure and efficient DevSecOps practices on Google Cloud. You'll learn how to secure your development pipeline with Google Cloud services like Artifact Registry, Cloud Build, Cloud Deploy, and Binary Authorization. This enables you to build, test, and deploy containerized applications with security controls throughout the CI/CD pipeline.
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。
完成在 Google Cloud 中实施 DevOps 工作流技能徽章中级课程, 展示您在以下方面的技能:利用 Cloud Source Repositories 创建 git 代码库; 在 Google Kubernetes Engine (GKE) 上启动、管理和扩缩 Deployment; 设计 CI/CD 流水线架构,以自动构建容器映像并将其部署到 GKE。 技能徽章是由 Google Cloud 颁发的专属数字徽章,旨在认可 您在 Google Cloud 产品与服务方面的熟练度;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。完成此技能 徽章课程和作为最终评估的实验室挑战赛,获得技能徽章, 在您的人际圈中炫出自己的技能。
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.
Learn about the fundamental features of Security Command Center on Google Cloud. Spend time in this course to understand assets, detection and compliance. Security Command Center is a key part of your Google Cloud security journey, complete these modules and quiz to earn a completion badge.
完成在 Cloud Run 上开发无服务器应用技能徽章中级课程, 展示您在以下方面的技能:集成 Cloud Run 与 Cloud Storage 以管理数据, 使用 Cloud Run 和 Pub/Sub 设计弹性异步系统架构, 构建依托 Cloud Run 技术的 REST API 网关,以及在 Cloud Run 上构建和部署服务。
完成在 Google Cloud 上部署 Kubernetes 应用技能徽章中级课程,展示您在以下方面的技能: 配置和构建 Docker 容器映像,创建和管理 Google Kubernetes Engine (GKE) 集群,利用 kubectl 实现高效 集群管理,以及按照稳健的持续交付 (CD) 实践部署 Kubernetes 应用。
Course four of the Anthos series prepares students to consider multiple approaches for modernizing applications and services within Anthos environments. Topics include optimizing workloads on serverless platforms and migrating workloads to Anthos. This course is a continuation of course three, Anthos on Bare Metal, and assumes direct experience with the topics covered in that course.
This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to on Google Cloud using Cloud Run.design, implement, deploy, secure, manage, and scale applications
完成在 Google Cloud 上使用 Terraform 构建基础设施技能徽章中级课程, 展示您在以下方面的技能:在使用 Terraform 时遵循基础设施即代码 (IaC) 原则;利用 Terraform 配置 来预配和管理 Google Cloud 资源;管理有效状态(本地和远程);以及将 Terraform 代码模块化,以方便重复使用和整理。
完成开发 Google Cloud 网络课程,赢取技能徽章。在此课程中,您将学习 部署和监控应用的多种方法,包括执行以下任务的方法:探索 IAM 角色并添加/移除 项目访问权限、创建 VPC 网络、部署和监控 Compute Engine 虚拟机、 编写 SQL 查询、在 Compute Engine 中部署和监控虚拟机,以及使用 Kubernetes 通过多种部署方法部署应用。
This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
This course teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud. Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
欢迎学习“Google Kubernetes Engine 使用入门”课程。Kubernetes 是位于应用和硬件基础架构之间的软件层,如果您对 Kubernetes 感兴趣,那就来对地方了!Google Kubernetes Engine 将 Kubernetes 作为 Google Cloud 上的代管式服务提供给您使用。 本课程的目标是介绍 Google Kubernetes Engine(通常称为 GKE)的基础知识,以及将应用容器化并在 Google Cloud 中运行的方法。本课程首先介绍 Google Cloud 的基础知识,然后概述容器、Kubernetes、Kubernetes 架构以及 Kubernetes 操作。
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。
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。
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。
“Google Cloud 基础知识:核心基础设施”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。
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.
完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据,展示以下技能: 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Dataproc 中创建集群和运行 Apache Spark 作业,以及调用机器学习 API,包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
完成构建安全的 Google Cloud 网络课程,赢取技能徽章。在此课程中,您将了解与网络有关的众多 资源,以便在 Google Cloud 上构建、扩缩和保护自己的应用。
完成“在 Google Cloud 上设置应用开发环境”课程,赢取技能徽章;通过该课程,您将了解如何使用以下技术的基本功能来构建和连接以存储为中心的云基础设施: Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。
完成入门级技能徽章课程为 Compute Engine 实现云负载均衡,展示以下方面的技能: 在 Compute Engine 中创建和部署虚拟机 以及配置网络和应用负载均衡器。
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This third course covers cloud automation and management tools and building secure networks.
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.