Naveen Rohith
Member since 2023
Gold League
42180 points
Member since 2023
本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具,可協助您透過 Google Cloud 使用 Google 產品和服務,開發、測試、部署及管理應用程式。有了 Gemini 的協助,您會學到如何開發和建構網頁應用程式、修正應用程式中的錯誤、開發測試及查詢資料。在實作研究室中,您也會體驗到 Gemini 如何改良軟體開發生命週期 (SDLC)。 Duet AI 已更名為 Gemini,這是我們的新一代模型。
本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具,可協助您透過 Google Cloud 保護雲端環境和資源。您將學到如何將工作負載範例部署到 Google Cloud 中的環境,以及運用 Gemini 找出並修復安全性設定錯誤。在實作研究室中,您也會體驗到 Gemini 如何改良雲端安全防護機制。 Duet AI 已更名為 Gemini,這是我們的新一代模型。
本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具,可協助管理員在 Google Cloud 佈建基礎架構。您將瞭解如何透過提示讓 Gemini 解釋基礎架構、部署 GKE 叢集,以及更新既有的基礎架構。在實作研究室中,您也會體驗到 Gemini 如何改良 GKE 的部署工作流程。 Duet AI 已更名為 Gemini,這是我們的新一代模型。
隨著企業持續擴大使用人工智慧和機器學習,以負責任的方式發展相關技術也日益重要。對許多企業來說,談論負責任的 AI 技術可能不難,如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術,本課程絕對能助您一臂之力。 您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談,協助貴機構奠定良好基礎,實踐負責任的 AI 技術。
這是一堂入門級的微學習課程,旨在探討大型語言模型 (LLM) 的定義和用途,並說明如何調整提示來提高 LLM 成效。此外,也會介紹多項 Google 工具,協助您自行開發生成式 AI 應用程式。
這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性,以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
Welcome to Qwiklabs Trivia for August! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the August badge.
完成「在 Cloud Storage 建立安全的資料湖泊」技能徽章入門課程,即可證明您具備下列技能: 保護及設定 Cloud Storage bucket、使用 Gemini 生成文字、管理 IAM 存取控管機制,以及建立 Knowledge Catalog 湖泊來治理資料。
完成「管理 Google Cloud 中的 Kubernetes」技能徽章中階課程, 即可證明您具備下列技能:使用 kubectl 管理部署作業、 在 Google Kubernetes Engine (GKE) 監控應用程式與偵錯,以及運用技術持續推送軟體更新。
完成「Google Cloud 監控工具」技能徽章入門課程, 即可證明您具備下列技能:使用 Cloud Monitoring 工具監控 Google Cloud 資源。
完成使用預訓練 API 實現語音和語言解決方案課程以獲得技能徽章,了解如何使用與語音相關的 API 工具來合成和轉錄語音。
完成「使用 Google Cloud Speech API」課程,即可獲得技能徽章。本課程將說明如何建立 Speech-to-Text API 要求、將音訊 及語音轉錄為文字。
完成「使用 Natural Language API 分析情緒」任務, 瞭解 API 如何從文字判斷情緒, 即可獲得技能徽章。
若想獲得技能徽章,請完成實現 Cloud Storage 和數據保護解決方案 技能徽章課程,您將在此瞭解如何建立 Cloud Storage bucket、 如何使用 Cloud Storage 指令列,以及如何在區塊中使用值區鎖定功能保護物件。
完成「搭配使用 API 和 Cloud Storage」 技能徽章入門課程,即可證明您具備下列技能: 搭配使用 API 和 Cloud Storage 資源,包括 Cloud Storage API。
完成「在 Google Cloud 使用機器學習 API」課程,即可獲得進階技能徽章。本課程說明以下機器學習和 AI 技術的基本功能: Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
完成「使用 Google API 分析語音和語言」課程, 瞭解如何將 Natural Language API 和 Speech API 投入實際應用, 即可獲得技能徽章。
完成「使用 Apps Script 整合 BigQuery 資料與 Google Workspace」技能徽章入門課程,即可證明您瞭解如何透過 AppSheet 將 Workspace 產品連結至 BigQuery。
完成透過 Google Cloud 建構網站技能徽章課程,即可獲得入門級技能徽章。 本課程以 Get Cooking in Cloud 系列影片為基礎, 涵蓋以下主題:在 Cloud Run 部署網站在 Compute Engine 託管網頁應用程式在 Google Kubernetes Engine 建立、 部署及擴充網站使用 Cloud Build 將單體式應用程式遷移至微服務架構
完成「建構安全的 Google Cloud 網路」課程,即可獲得技能徽章。本課程將說明多項網路相關 資源,協助您在 Google Cloud 建構、調度資源和保護應用程式。
For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.
完成 雲端架構:設計、實作與管理 課程即可獲得 技能徽章,證明您具備下列技能: 使用 Apache 網路伺服器部署可公開存取的網站、使用開機指令碼設定 Compute Engine VM、 使用 Windows 防禦主機和防火牆規則設定安全的 RDP、建構 Docker 映像檔並部署至 Kubernetes 叢集,然後進行更新,以及建立 Cloud SQL 執行個體並匯入 MySQL 資料庫。 這個技能徽章課程是絕佳的 資源,可讓您瞭解Google Cloud 認證專業雲端架構師認證測驗涵蓋的主題。
完成 在 Google Cloud 實作 DevOps 工作流程 技能徽章中階課程, 即可證明您具備下列技能:建立與管理 Git 存放區、 在 Google Kubernetes Engine (GKE) 發布、管理和調度 Deployment, 以及建立 CI/CD 管道,自動建構容器映像檔與執行 GKE 部署作業。
完成 使用 Firebase 開發無伺服器應用程式 技能徽章中階課程, 即可證明您具備下列技能:使用 Firebase 架構及建構無伺服器的網頁應用程式、 運用 Firestore 管理資料庫、使用 Cloud Build 自動部署內容, 以及將 Google 助理功能整合至應用程式。
完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程, 即可證明自己具備下列知識與技能:運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline; 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載, 以及使用 BigQuery ML 建構機器學習模型。
Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!
The world around us is changing and mastering future-driven technologies is the key to success. We want you to get started by learning a little of everything! Discover machine learning in data analysis, build scalable cloud solutions and accelerate software development that will shape the future. The possibilities in the Arcade are endless and all of those will lead you towards earning your first Google Cloud Credential. No prior experience required.
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
在本課程中,您將透過實際操作,瞭解如何在 Looker 應用進階 LookerML 概念。您將學習如何使用 Liquid 自訂和建立動態維度 和測量指標、建構動態 SQL 衍生資料表和自訂的原生衍生資料表, 並運用擴充參數將 LookML 程式碼模組化。
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.
完成 Looker 資料模型管理技能徽章中階課程,即可證明您具備下列技能:維護 LookML 專案的健全性、運用 SQL Runner 驗證資料、採用 LookML 最佳做法、改良查詢及 報表,並執行永久衍生資料表和快取政策。
完成「在 Looker 建構 LookML 物件」技能徽章入門課程, 即可證明您具備下列技能: 建立新的維度和測量指標、檢視畫面和衍生資料表;根據需求設定測量指標篩選器和類型; 更新維度和測量指標; 建構及調整「探索」;將檢視表彙整至現有「探索」;以及配合業務需求決定要建立哪些 LookML 物件。
完成「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程,即可證明您具備下列技能: 可使用 BigQuery ML 建立及評估機器學習模型,並根據資料進行預測。
完成使用 Cloud Vision API 分析圖片課程,即可獲得技能徽章。本課程說明如何運用 Cloud Vision API 執行各種工作,包括擷取圖片中的文字。
完成「設定 Google Cloud 網路」課程,即可獲得技能徽章。 您將瞭解如何在 Google Cloud Platform 執行基本的網路工作,包括建立自訂網路、新增子網路防火牆規則,還有建立 VM 並測試 VM 之間的通訊延遲。
完成「充實中繼資料及發掘 Lakehouse 資料」技能徽章課程,即可證明您具備 BigQuery、 Lakehouse 和 Knowledge Catalog 的相關技能。您會建立 Lakehouse 資料表,並充實中繼資料管理和資料表資料探索功能。
完成「保護 Lakehouse 資料」技能徽章入門課程,即可證明您具備下列技能:在 Knowledge Catalog 中使用 IAM、BigQuery、 Lakehouse 和 Data Catalog,建立並保護 Lakehouse 資料表。
Welcome to Qwiklabs Trivia for July! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the July badge.
完成 在 Google Cloud 實作 Sensitive Data Protection 技能徽章入門課程,證明您具備下列技能:使用 Sensitive Data Protection 服務 (包括 Cloud Data Loss Prevention API) 來檢查、遮蓋及去識別化 Google Cloud 中的機密資料。
The demand for data skills is growing rapidly, and we want you to get ahead! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. There are a lot of different aspects to any data role, so it's important to start with the basics - and we’ve got you covered. Learn how to tap into ML APIs, dive into your first data lake, and learn how the experts think about securing data. No experience required.
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.
完成 從 BigQuery 資料取得深入分析結果 技能徽章入門課程,即可證明您具備下列技能: 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤,以及在 Data Studio 中 透過連結 BigQuery 資料建立報表。
完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程,即可證明您具備下列技能: 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Managed Service for Apache Spark 建立叢集和執行 Apache Spark 工作,以及呼叫機器學習 API,包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
完成「為 Looker 資訊主頁和報表準備資料」技能徽章入門課程, 即可證明您具備下列技能:可篩選、排序和 pivot 資料、合併不同的 Looker 探索結果, 還能使用函式和運算子建構 Looker 資訊主頁和報表,取得資料分析結果和圖表。
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.
Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
Demand for cloud-skilled workers is rising. According to a report by Indeed, cloud computing jobs are expected to grow by 22% over the next five years, much faster than the average for all occupations. Play now to get hands-on experience building with Google Cloud's powerful coding and infrastructure management tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.
完成「Google Cloud Compute 基本操作」任務, 學習如何在 Compute Engine 中使用虛擬機器 (VM)、永久磁碟 和網路伺服器,即可獲得技能徽章。
Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.
完成「在 Google App Engine 上部署及管理應用程式」課程,即可獲得技能徽章。本課程將說明如何搭配 Python、Go 和 PHP 使用 App Engine。
The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
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.
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.
這個入門微學習課程主要說明生成式 AI 的定義和使用方式,以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具,協助您開發自己的生成式 AI 應用程式。