Vertex AI is now Gemini Enterprise Agent Platform! We are currently updating our content to reflect this change. Please bear with us if you encounter naming inconsistencies during this transition.
Sarvesh Sarvesh
成为会员时间：2024
钻石联赛
64920 积分
为 Compute Engine 实现云负载均衡
Earned Jan 10, 2025 EST
Google Cloud 云计算基础知识
Earned Dec 31, 2024 EST
监控和管理 Google Cloud 资源
Earned Dec 31, 2024 EST
Google Cloud 中的监控功能
Earned Dec 31, 2024 EST
使用 Natural Language API 分析情感
Earned Dec 30, 2024 EST
在 Cloud Storage 上创建安全的数据湖
Earned Dec 30, 2024 EST
保护 BigLake 数据
Earned Dec 30, 2024 EST
实现 Cloud Storage 和数据保护解决方案
Earned Dec 30, 2024 EST
实现事件驱动的即时消息和自动化工作流
Earned Dec 30, 2024 EST
Configure your Workplace: Google Workspace for IT Admins
Earned Dec 30, 2024 EST
实现云协作和生产力工作流
Earned Dec 29, 2024 EST
在 Google 表格中使用函数、公式和图表
Earned Dec 29, 2024 EST
使用 Google API 分析语音和语言
Earned Dec 28, 2024 EST
在 BigQuery 中执行预测性数据分析
Earned Dec 28, 2024 EST
在 Google Cloud 上使用 TensorFlow 进行图片分类
Earned Dec 28, 2024 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Dec 27, 2024 EST
Exploring Vertex AI Search for Retail
Earned Dec 27, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned Dec 27, 2024 EST
Build deterministic Virtual Agent enhanced with data stores
Earned Dec 26, 2024 EST
Build Streaming Data Pipelines on Google Cloud
Earned Nov 9, 2024 EST
Build and Deploy a Generative AI solution using a RAG framework
Earned Nov 6, 2024 EST
图像生成简介
Earned Nov 2, 2024 EDT
Vertex AI Studio 简介
Earned Nov 2, 2024 EDT
Generative AI Fundamentals
Earned Nov 2, 2024 EDT
Text Prompt Engineering Techniques
Earned Nov 2, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Nov 1, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Nov 1, 2024 EDT
创建图片标注模型
Earned Oct 29, 2024 EDT
Transformer 模型和 BERT 模型
Earned Oct 29, 2024 EDT
编码器-解码器架构
Earned Oct 29, 2024 EDT
负责任的 AI 简介
Earned Oct 29, 2024 EDT
注意力机制
Earned Oct 29, 2024 EDT
使用 BigQuery 构建数据仓库
Earned Oct 8, 2024 EDT
Build Batch Data Pipelines on Google Cloud
Earned Oct 1, 2024 EDT
Production Machine Learning Systems
Earned Sep 6, 2024 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Sep 1, 2024 EDT
通过 BigQuery ML 创建机器学习模型
Earned Aug 28, 2024 EDT
Transform and Clean your Data with Dataprep by Alteryx on Google Cloud
Earned Aug 27, 2024 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned Aug 26, 2024 EDT
在 Google Cloud 上为机器学习 API 准备数据
Earned Aug 25, 2024 EDT
Machine Learning in the Enterprise
Earned Aug 23, 2024 EDT
Feature Engineering
Earned Aug 19, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Aug 11, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Aug 10, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned Aug 1, 2024 EDT
Launching into Machine Learning
Earned Aug 1, 2024 EDT
Google Cloud 上的 AI 和机器学习简介
Earned Jul 20, 2024 EDT
Earn a skill badge by completing the Configure your Workplace: Google Workspace for IT Admins quest, where you will get try out the Admin role for Workspace and learn to provision Groups, manage applications, security, and manage Meet. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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完成 实现云协作和生产力工作流课程，赢取入门技能徽章。在此课程中，您将了解 Google 的协作平台 并学习如何使用 Gmail、Google 日历、Meet、Google 云端硬盘、Google 表格和 AppSheet。
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完成中级技能徽章课程“在 Google 表格中使用函数、公式和图表”， 展现您在以下方面的技能：使用函数分析数据；使用图表直观呈现数据；以及搜索和验证数据、 设置数据格式、显示数据。
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完成使用 Google API 分析语音和语言课程，赢取技能徽章 。在此课程中，您将学习如何在真实场景中使用 Natural Language API 和 Speech API。
完成“在 Google Cloud 上使用 TensorFlow 进行图片分类”课程，赢取中级技能徽章 。在此课程中，您将学习如何使用 TensorFlow 和 Vertex AI 来创建和训练机器学习模型。您将主要使用 Vertex AI Workbench 上用户管理的 笔记本。
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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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This course provides hands-on experience with Google Cloud's Search for Retail, focusing on practical skills in setting up and managing retail search functionalities using APIs and console configurations. Participants will engage with real-world scenarios to learn how to import product data, manage user events, configure search parameters, and optimize search results within a retail environment.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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Demonstrate the ability to create and deploy deterministic virtual agents using Dialgflow CX and augment responses by grounding results on your own data integrating with Vertex AI Agent Builder data stores and leveraging Gemini for summarizations.
You will use the following technologies and Google Cloud services:
Vertex AI Agent Builder
Dialogflow CX
Gemini
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.
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本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学，特别是热力学。过去几年内，扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论，以及如何在 Vertex AI 上训练和部署此类模型。
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本课程介绍 Vertex AI Studio，这是一种用于与生成式 AI 模型交互、围绕业务创意进行原型设计并在生产环境中落地的工具。通过沉浸式应用场景、富有吸引力的课程和实操实验，您将探索从提示到产品的整个生命周期，了解如何将 Vertex AI Studio 用于多模态 Gemini 应用、提示设计、提示工程和模型调优。本课程的目的在于帮助您利用 Vertex AI Studio，在自己的项目中充分发掘生成式 AI 的潜力。
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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随着企业对人工智能和机器学习的应用越来越广泛，以负责任的方式构建这些技术也变得更加重要。但对很多企业而言，真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI，本课程正适合您。
本课程将介绍 Google Cloud 目前如何践行 Responsible AI，以及从中总结的最佳实践和经验教训，便于您以此为框架构建自己的 Responsible AI 方法。
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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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.
了解详情
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。
了解详情
完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型，展示您在以下方面的技能： 使用 BigQuery ML 创建和评估机器学习模型，以执行数据预测。
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Dataprep is Google's self-service data preparation tool built in collaboration with Alteryx. Learn the basics of cleaning and preparing data for analysis and visualization, all in the Google ecosystem. In this course, you will learn how to connect Dataprep to your data in Cloud Storage and BigQuery, clean data using the interactive UI, profile the data, and publish your results back into the Google ecosystem. You will learn the basics of data transformation, including filtering values, reshaping the data, combining multiple datasets, deriving new values, and aggregating your dataset.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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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。
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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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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) 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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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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本课程介绍 Google Cloud 的 AI 和机器学习 (ML) 能力，重点讲解如何开发生成式和预测式 AI 项目。本课程将探讨“数据到 AI”全生命周期中的多种技术、产品和工具，并通过互动练习帮助数据科学家、AI 开发者和机器学习工程师提升专业能力。
为 Compute Engine 实现云负载均衡
Earned Jan 10, 2025 EST
Google Cloud 云计算基础知识
Earned Dec 31, 2024 EST
监控和管理 Google Cloud 资源
Earned Dec 31, 2024 EST
Google Cloud 中的监控功能
Earned Dec 31, 2024 EST
使用 Natural Language API 分析情感
Earned Dec 30, 2024 EST
在 Cloud Storage 上创建安全的数据湖
Earned Dec 30, 2024 EST
保护 BigLake 数据
Earned Dec 30, 2024 EST
实现 Cloud Storage 和数据保护解决方案
Earned Dec 30, 2024 EST
实现事件驱动的即时消息和自动化工作流
Earned Dec 30, 2024 EST
Configure your Workplace: Google Workspace for IT Admins
Earned Dec 30, 2024 EST
实现云协作和生产力工作流
Earned Dec 29, 2024 EST
在 Google 表格中使用函数、公式和图表
Earned Dec 29, 2024 EST
使用 Google API 分析语音和语言
Earned Dec 28, 2024 EST
在 BigQuery 中执行预测性数据分析
Earned Dec 28, 2024 EST
在 Google Cloud 上使用 TensorFlow 进行图片分类
Earned Dec 28, 2024 EST
利用 BigQuery ML 构建预测模型时的数据工程处理
Earned Dec 27, 2024 EST
Exploring Vertex AI Search for Retail
Earned Dec 27, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned Dec 27, 2024 EST
Build deterministic Virtual Agent enhanced with data stores
Earned Dec 26, 2024 EST
Build Streaming Data Pipelines on Google Cloud
Earned Nov 9, 2024 EST
Build and Deploy a Generative AI solution using a RAG framework
Earned Nov 6, 2024 EST
图像生成简介
Earned Nov 2, 2024 EDT
Vertex AI Studio 简介
Earned Nov 2, 2024 EDT
Generative AI Fundamentals
Earned Nov 2, 2024 EDT
Text Prompt Engineering Techniques
Earned Nov 2, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Nov 1, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Nov 1, 2024 EDT
创建图片标注模型
Earned Oct 29, 2024 EDT
Transformer 模型和 BERT 模型
Earned Oct 29, 2024 EDT
编码器-解码器架构
Earned Oct 29, 2024 EDT
负责任的 AI 简介
Earned Oct 29, 2024 EDT
注意力机制
Earned Oct 29, 2024 EDT
使用 BigQuery 构建数据仓库
Earned Oct 8, 2024 EDT
Build Batch Data Pipelines on Google Cloud
Earned Oct 1, 2024 EDT
Production Machine Learning Systems
Earned Sep 6, 2024 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Sep 1, 2024 EDT
通过 BigQuery ML 创建机器学习模型
Earned Aug 28, 2024 EDT
Transform and Clean your Data with Dataprep by Alteryx on Google Cloud
Earned Aug 27, 2024 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned Aug 26, 2024 EDT
在 Google Cloud 上为机器学习 API 准备数据
Earned Aug 25, 2024 EDT
Machine Learning in the Enterprise
Earned Aug 23, 2024 EDT
Feature Engineering
Earned Aug 19, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Aug 11, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Aug 10, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned Aug 1, 2024 EDT
Launching into Machine Learning
Earned Aug 1, 2024 EDT
Google Cloud 上的 AI 和机器学习简介
Earned Jul 20, 2024 EDT