Francisco Colomer
Member since 2023
Diamond League
61070 points
Member since 2023
您已建立具有進階設定功能的代理,可開始賦予代理實際應用能力。為代理配備工具,使代理能搜尋網路、執行程式碼、查詢資料庫和執行自訂動作。將代理從聰明的回覆者,轉變為能採取行動的得力助手。
您已建構能回覆查詢的基本 LLM 代理,是時候讓代理有狀態。利用工作階段狀態建構能維持對話脈絡、記住使用者偏好,並提供個人化體驗的代理。將代理從無狀態的回覆者轉為智慧助理。
您已經成功打造第一個代理,是時候迎接更進階的挑戰。在本課程中,您將學習如何應用進階指令、選擇模型、建立規劃能力及結構化輸出模式,藉此將基本 AI 代理轉為高明又精確的助理,讓您的技能更上一層樓。加入社群論壇,提出問題並參與討論
步入代理式策略的未來:探索、設計與原型建立本課程可協助您精通 Google 代理式 AI 轉型框架,並將聊天機器人轉變為自動化團隊夥伴。您將透過零售應用實例,瞭解如何量化商業價值、排定 AI 專案的優先順序、規劃關鍵使用者歷程,並透過 Google AI Studio 和 Gemini Enterprise 等無程式碼工具建構可運作的原型。此課程提供穩定的學習藍圖,可協助企業和技術主管帶領組織踏入代理式 AI 的時代。
在本課程中,您將學習如何在 Google Antigravity 中自動調度管理代理程式,以驚人的速度建構軟體。這堂實作課程會先引導您安裝 Antigravity 並開始使用,接著,您將使用 Firebase 啟用服務,以透過 Antigravity 建構應用程式。最後,您將提示 Antigravity 中的代理程式平行運作,打造出 Voyager 電玩遊戲。
完成「在 Google Cloud 使用 Terraform 建構基礎架構」技能徽章中階課程, 即可證明自己具備下列知識與技能:使用 Terraform 的基礎架構即程式碼 (IaC) 原則、運用 Terraform 設定佈建及管理 Google Cloud 資源、有效管理狀態 (本機和遠端),以及將 Terraform 程式碼模組化,以利重複使用和管理。
Complete the Design Secure Landing Zones and Architecture skill badge to demonstrate your proficiency in auditing and hardening Google Cloud environments. Emphasis is placed on the 'Red Team / Blue Team' dynamic—you will inherit a live, non-compliant infrastructure and must identify security gaps (IAM, Network, Data) before applying remediation 'as code' or via the console to meet strict financial industry standards. 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 assessment challenge lab to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
In this advanced challenge lab, you act as a Data Engineer for Cymbal Direct, a retail company integrating real-time movie review data into a marketing pipeline. You are responsible for building two distinct streaming architectures. First, you will implement a direct, code-free ingestion path using Pub/Sub BigQuery subscriptions. Second, you will deploy a sophisticated Dataflow pipeline that uses JavaScript User-Defined Functions (UDFs) to transform raw text into numerical data before it reaches BigQuery, all while managing high-velocity data generated by a simulated stream.
Complete the Orchestrate Data Lifecycle Automation with Data Agents skill badge to demonstrate your proficiency in modernizing data infrastructure using AI-driven automation. Emphasis is placed on acting as an 'Agent Orchestrator'—leveraging specialized Data Agents to build resilient Dataform pipelines, enforce Dataplex governance, and accelerate data science workflows in Colab Enterprise. 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 assessment challenge lab to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
In this introductory course, you'll learn how Looker can help you explore, analyze, and visualize your data to drive better decisions. Through a combination of video lectures and demos, you'll discover how to connect to various data sources, build interactive dashboards, and perform effective data analysis. Whether you're a data analyst, BI analyst, data scientist or business user, this course will equip you with the foundational knowledge to start using Looker effectively, regardless of your background.
建立您的第一個 Gemini Enterprise 應用程式,獲得技能徽章!將各種資料來源連接到您的應用程式,建立強大的統合式搜尋和分析引擎。掌握 Deep Research 代理、多代理構思和 NotebookLM 等進階功能,進行重點分析。
瞭解 AI 代理如何發揮更高的業務影響力,包括根據您的 KPI 規劃要使用的代理類型,以及探索能解決實際瓶頸的用途。您也將認識各種無程式碼到高程式碼解決方案,瞭解 Gemini Enterprise 如何協助建構和自動調度合適的代理。
本課程介紹 AI 代理的基礎知識,並探討代理的實際應用價值。代理可為開發人員、架構師和技術決策者奠定基礎,協助他們從目標導向的自主行為角度來理解 AI 系統。
瞭解 AI 代理的概念,探索代理如何藉由自主行動及推論解決複雜問題。您將瞭解代理如何透過模型、工具和調度管理程序等技術架構,助您學習、規劃和實現目標。
This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.
In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.
瞭解如何使用 Agent Development Kit (ADK),建構複雜的 AI 代理並用於正式環境。本課程介紹 ADK 的開放原始碼框架,包括簡單的提示工程,以及程式碼優先的結構化軟體開發做法 (適用於企業級多代理系統)。
完成「透過 Google AI Studio 開發 AI 輔助原型」技能徽章入門課程,證明您具備下列技能:編寫有效的提示詞、運用多模態功能分析圖像和影片、 依據範本和文字提示詞設計可運作的 AI 應用程式原型,以及使用 API 金鑰建構及部署自訂 AI 解決方案。
In this video, you'll learn to use Gemini in Google Sheets for advanced data analysis. You'll learn how to create data visualizations, like a scatter plot, using a simple prompt. You'll also learn how to ask Gemini to analyze your data for strategic insights and recommendations, such as how to save money.
In this video, you'll learn to use Gemini in Google Sheets to automatically generate organized trackers from unstructured data. You'll learn how to write a prompt that references other Google Drive files using the "@" symbol. You'll also see how Gemini builds a fully formatted, color-coded table with drop-down menus based on the data in your notes, saving you significant manual effort.
這部影片說明如何使用 Gmail 內建 Gemini 管理 Google 日曆,包括在側邊面板詢問行程,以及一鍵將在電子郵件中偵測到的活動新增至日曆。
In this video, you'll learn to use Gemini in Google Slides to build polished presentations efficiently. You'll see how to create slides by referencing content directly from your Google Drive files using the "@" symbol. You'll also learn to generate custom, professional images from a simple text prompt to visually enhance your presentation.
In this video, you'll learn to use the "Ask Gemini" feature in Google Sheets to manage your data with natural language. You'll see how to ask Gemini to create dropdowns, highlight sales data, create a pivot table, filter by month, and sort by revenue.
In this video, you'll learn to use the =AI() function in Google Sheets to automate your work. You'll see how to generate text like slogans, summarize paragraphs of customer feedback, and categorize data by classifying inquiries and analyzing sentiment.
In this video, you'll learn to create "what if" scenarios using AI's reasoning. You'll see how to set a "before" scene with a person holding a cake, prompt an action by asking "what would happen if they tripped?", and let the AI generate the plausible "after" image of the cake falling.
In this video, you'll learn the "creative mashup artist" technique for combining images. You'll see how to generate a subject and a scene as two separate images, and then use a final blending prompt to fuse the astronaut from the first image and the court from the second into one new picture.
In this video, you'll learn to art direct your images in the Gemini app. You'll see how to use multi-turn editing to furnish an empty room step-by-step, and how to "remix" a photo by applying the color and texture of a butterfly's wings to a pair of rainboots.
In this video, you'll learn to create imaginative portraits in the Gemini app that maintain your likeness. You'll see how to use the "Subject, Action, Scene, Style" formula for better prompts, transport yourself into a vintage photo, and combine a photo of yourself and your dog into one new image.
In this video, you'll learn to use NotebookLM to manage a large-scale research project. You'll see how to upload all your documents to get summaries, ask deeper strategic questions to find key insights, and use the audio feature to listen to your findings on the go.
In this video, you'll learn to use NotebookLM to analyze raw data and find compelling stories. You'll see how to ground the AI in your specific documents, prompt it to generate newsworthy PR claims, and ask it to find hidden correlations between different data points to uncover new insights.
這部影片說明如何使用 AI 助理規劃大型團隊活動,包括腦力激盪、後勤安排,以及分析活動後意見回饋。
這部影片介紹使用 Gemini Deep Research 的專家級提示,包括如何指派角色、指定輸出格式,以及引導搜尋以進行全面的競爭分析。
In this video, you'll learn to use Gemini Deep Research to make complex purchasing decisions with confidence. You'll see how to write a nuanced, personal prompt about your specific needs and receive a synthesized, comparative report that cuts through the clutter of online reviews.
In this video, you'll learn to create an animated bar chart race using Gemini Canvas. You'll see how to write a prompt to visualize data over time and then use a follow-up prompt to refine the animation, such as slowing it down for a presentation.
這部影片說明如何在 Gemini Canvas 中使用描述性文字提示詞,生成複雜的動畫視覺藝術,例如動態排版。
In this video, you'll learn to build a reusable, custom "Study Guide Gem." You'll see how to write the core instructions for your Gem once, and then use it again and again to transform messy notes and articles into a perfectly structured study guide with a summary, outline, and glossary.
這部影片說明如何將個人筆記上傳至 Gemini Canvas,並使用簡單的提示詞,建立包含各種題型的互動式測驗。
In this video, you'll learn to use Gemini Deep Research to conduct competitive marketing analysis. You'll see how to submit a research prompt, approve the personalized research plan Gemini creates, and receive a detailed, synthesized report on competitor campaigns to inform your strategy.
In this video, you'll learn to build a working prototype of a personalized weather app using Gemini Canvas. You'll see how to specify the cities for a 7-day forecast and then use a follow-up prompt to change the app's theme to a minimal, dark mode interface.
這部影片說明如何在 Gemini Canvas 使用簡單的文字提示詞,建構互動式 3D 太陽系模擬,並加入教育功能。
這部影片說明如何建立自訂個人「公用程式」應用程式 (例如番茄鐘計時器),只要在 Gemini Canvas 中輸入簡單提示詞,描述功能和設計即可。
In this video, you'll learn to use the Guided Learning experience in Gemini to build a deep understanding of any topic. You'll see how to start a conversation, engage with Gemini's probing questions, and use interactive tools like diagrams and quizzes to guide your learning journey.
這部影片說明如何在 Gemini Canvas 中使用簡單的提示詞,建構、自訂及分享可玩的遊戲,例如井字遊戲。
這部影片將說明如何使用 Gemini Deep Research 和創意提示詞,將複雜資訊轉化為有趣的個人化分析,例如運動球探報告和對戰表。
這部影片將說明如何使用 Gemini Canvas 的「建立」選單,將大篇幅文字立即轉換成資訊圖表和網頁等視覺素材。
這部影片說明如何使用 Gemini Canvas,透過「直覺式程式開發」技術,將簡單的應用程式繪圖轉化為可運作的原型。
This video covers how NotebookLM's Reports feature dynamically suggests formats to help you create customized, trustworthy analyses of your documents with ease.
這部影片說明如何使用 Gemini Gem 建構個人化的「工作夥伴」代理,簡化基本意見回饋,讓會議更具策略性且更有效率。
這部影片將說明如何使用 Gemini Advanced 研究主題、製作簡報大綱,以及使用 Google 文件內建 Gemini 生成談話要點。
This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.
This video covers how to use NotebookLM for common marketing tasks like analyzing customer feedback, conducting market research, and generating content ideas.
This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.
This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.
This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.
This video covers how to use NotebookLM as a personal research assistant by adding sources, asking questions, and generating new content formats based on your documents.
這部影片說明如何使用 Gmail 內建 Gemini 撰寫新郵件草稿、調整語氣、根據雲端硬碟檔案內容回覆,以及使用智慧回覆建議。
這部影片說明如何使用 Google 文件中的「幫我建立」功能。這項功能會參考雲端硬碟中其他檔案的內容,生成已設定格式的完整文件。
This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
這部影片說明如何使用 Gmail 內建 Gemini 歸納電子郵件重點、尋找資訊及草擬回覆,更有效率地管理收件匣。
這部影片說明如何使用 Google 簡報內建 Gemini,自動生成會議回顧並草擬後續追蹤電子郵件,協助簡化會後流程並節省時間。
這部影片將說明如何運用 Google 試算表中的 Gemini 進階 AI 功能,在幾分鐘內輕鬆提取資料並生成洞察,完全不需要任何技術或程式設計背景。
這部影片將說明如何運用 Gemini Gem,以主管獨特的口吻撰寫真實自然的社群媒體貼文。瞭解如何運用寫作範例和明確指令訓練 Gem,克服擴大高階主管社群媒體影響力的難題。瞭解如何快速生成引人入勝的貼文,在節省時間的同時,強化思維領導力並確保真實性。
這部影片將說明如何建立自己的 Brevity Gem,將雜亂的筆記或長篇文件轉化為簡潔明瞭的內容提要,方便高階主管查看。
這部影片說明如何使用 Gemini 和 Apps Script,在 Google Workspace 中自動執行手動工作。您將學習如何提示 Gemini 生成 Apps Script 程式碼,在 Google 試算表中針對未標示為「完成」的工作,自動草擬電子郵件提醒。即使幾乎沒有技術專業知識,也能自動化工作流程,省下時間處理更重要的工作,不必再手動後續追蹤。
This video covers how you can leverage Notebook LM to "eat the frog" on your to-do list by automating complex tasks like summarizing legislation and mapping services, saving you hours of work.
這部影片將說明如何運用 Gemini 消除繁瑣的手動資料輸入作業。瞭解如何拍攝資料相片或螢幕截圖 (來自 PDF、紙本或圖片),並提示 Gemini 立即將資料轉換為結構化的 Google 試算表。瞭解這個簡單的訣竅,省下無數轉錄資料的時間,讓 Gemini 成為您的個人資料輸入助理。只要拍照、輸入提示,然後匯出即可!
這部影片將說明如何運用 AI 找出策略中的弱點和隱藏假設。您將學到「找出漏洞」法,也就是透過 AI 提示詞,輕鬆對計畫進行壓力測試,找出漏洞並強化策略思維。
This video will cover how to use NotebookLM to gather and analyze publicly available information, combine it with internal documents, and extract key competitive insights.
這部影片說明如何在 Google Workspace 中,打造個人化 Gemini 搜尋結果。可瞭解如何使用「@」符號,將文件和研究論文直接納入提示,取得更符合需求的 AI 輸出內容。
這部影片將說明如何使用 Gemini 重點摘要 Google Workspace 中的長篇文件,助您快速取得所需資訊並節省時間。您將瞭解如何使用 Gemini 摘要整份文件或所選文字,以及如何使用 雲端硬碟內建 Gemini 總結多個檔案。
這部影片介紹提示工程的基本概念,協助您與 AI 有效互動。學習簡單的框架 (角色、任務、情境、格式),撰寫清晰的提示詞,讓 Gemini in Google Workspace 更快提供更優質的結果。瞭解如何使用自然語言、具體說明需求,以及透過反覆調整來獲得最佳 AI 輔助。
這部影片將說明如何運用 Gemini 版 Google 文件的進階 AI 功能,發想點子、草擬各種行銷內容,並與團隊順暢協作。
This video covers how NotebookLM can revolutionize customer insight gathering from call or chat transcripts. You'll learn to upload PDF transcripts of hundreds of conversations (even multilingual ones!) and quickly extract key themes, trending topics, and actionable insights without listening for hours. Discover how to save findings, share notebooks, and even generate interactive podcast summaries of your data.
這部影片說明如何建立專屬的 Gemini Gem,運用進階 AI 功能自動處理重複性工作,大幅提升工作效率。
In this course, you'll learn how to build software with Gemini, Google’s generative AI. The best part is: Anyone can do this. It’s okay if you've never written code before. You just need to be curious and motivated, and we'll help you get from zero to app.
這部影片說明如何在 Gemini Canvas 中使用簡單的文字提示詞,打造一台具備自訂控制項和可彈奏鍵盤的全互動式音樂合成器。
完成「透過直覺式程式開發和 MCP,建構智慧雲端應用程式」課程,即可獲得技能徽章。在本課程中,您將學會如何利用 Google AI 程式設計助理和 MCP 伺服器的強大功能。
Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime. 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 assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
這門課程適合應用程式開發人員和 DevOps 工程師,您將學會如何運用 Gemini CLI (終端機適用並採用 Gemini 技術的生成式 AI 代理),以更聰明的方式處理工作。這門課程會說明 Gemini CLI 的安裝方式與設定、介紹用途和安全性最佳做法,並解釋指令、工具、MCP 伺服器和擴充功能。在實作練習,您會安裝及設定 Gemini CLI,藉此分析程式碼,還有建構及修改應用程式。
歡迎來到「AI 基礎架構:網路技術」課程。本課程將說明如何運用 Google Cloud 的高頻寬、低延遲基礎架構,最佳化調整 AI 系統所有元件之間的資料傳輸和通訊。最後,您將掌握網路在整個 AI 管道 (從資料擷取、訓練到推論) 發揮的關鍵作用,並採取最佳做法,確保工作負載能以最高速度運作。
在本課程中,您將全面瞭解 Google Cloud 提供的儲存空間解決方案,專門用於 AI 和高效能運算 (HPC) 的工作負載。您將學習如何根據機器學習生命週期的各個階段,選擇合適的儲存空間;以及探索如何在訓練期間將 I/O 效能最佳化、管理準備資料所需的龐大資料集,以及用低延遲提供模型構件。透過實際例子和示範,您將掌握專業知識,得以設計穩健的儲存空間解決方案,並加快 AI 創新。
這堂課程會完整說明如何在 Google Cloud 部署、管理及最佳化調整 AI 和高效能運算 (HPC) 工作負載。藉由一系列課堂和實務示範,您會瞭解不同的部署策略,從使用 Google Compute Engine (GCE) 的高度可自訂環境,到 Google Kubernetes Engine (GKE) 等代管解決方案。具體來說,您會學到如何建立叢集及部署 GKE,以便執行推論工作。
歡迎來到 Cloud TPU 課程。我們將探討在各種情境下使用 TPU 的優缺點,並比較不同的 TPU 加速器,協助您選擇合適的工具。您將瞭解如何盡可能提高 AI 模型的效能和效率,以及互通的 GPU/TPU 對於打造靈活的機器學習工作流程有多重要。我們會透過引人入勝的內容和實際演示,一步步引導您有效運用 TPU。
想瞭解 AI 背後的強大硬體嗎?本單元將深入解析針對效能最佳化的 AI 電腦,說明其重要性。我們將探討 CPU、GPU 和 TPU 如何大幅加速 AI 任務運算,分析各自的特點,以及 AI 軟體如何充分利用這些硬體效能。單元結束後,您將清楚掌握如何根據 AI 專案挑選合適的 GPU,並做出明智的 AI 工作負載決策。
準備開始使用 AI Hypercomputer 了嗎?這門課程可讓您快速上手!我們將介紹這個架構的基本概念,以及此架構如何幫助 AI 處理 AI 工作負載。您將瞭解 Hypercomputer 內的不同元件,例如 GPU、TPU 和 CPU,以及如何視需求選擇合適的部署方法。
In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
The course aims to train Google technical sales partners on the business value discovery process using proprietary content.
Want to learn more about Google Cloud? Grow your Google Cloud knowledge, strengthen your skills to win with customers, and scale your Google Cloud business. Find it here in one handy location.
This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.
完成建立及管理 AlloyDB 執行個體技能徽章入門課程, 即可證明自己具備下列技能:執行主要 AlloyDB 作業 和工作、從 PostgreSQL 遷移至 AlloyDB、管理 AlloyDB 資料庫,以及 使用 AlloyDB 資料欄引擎加快數據分析查詢。
完成「建立及管理 Bigtable 執行個體」技能徽章入門課程,證明您具備下列技能:建立執行個體、設計結構定義、 查詢資料,以及在 Bigtable 執行管理工作,包括監控效能、設定自動調度節點資源和複製作業。
完成「建立及管理 Cloud Spanner 執行個體」技能徽章入門課程,即可證明自己具備下列技能: 建立 Cloud Spanner 執行個體和資料庫,並與其互動; 使用各種技術載入 Cloud Spanner 資料庫; 備份 Cloud Spanner 資料庫;定義結構定義及瞭解查詢計畫;以及 部署連線至 Cloud Spanner 執行個體的現代化網頁應用程式。
完成建立及管理 PostgreSQL 適用的 Cloud SQL 執行個體技能徽章入門課程,證明您具備下列技能:遷移、設定和管理 PostgreSQL 適用的 Cloud SQL 執行個體和資料庫。
本課程會介紹 Vertex AI Studio。您可以運用這項工具和生成式 AI 模型互動、根據商業構想設計原型,並投入到正式環境。透過身歷其境的應用實例、有趣的課程及實作實驗室,您將能探索從提示到正式環境的生命週期,同時學習如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計、提示工程和模型調整。這個課程的目標是讓您能運用 Vertex AI Studio,在專案中發揮生成式 AI 的潛能。
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。
This course introduces you to the world of reliable deep learning, a critical discipline focused on developing machine learning models that not only make accurate predictions but also understand and communicate their own uncertainty. You'll learn how to create AI systems that are trustworthy, robust, and adaptable, particularly in high-stakes scenarios where errors can have significant consequences.
完成 使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL 技能徽章入門課程,證明您具備下列技能: 使用「資料庫遷移服務」中各種可用的工作類型和連線選項, 將 MySQL 資料遷移至 Cloud SQL,以及在執行「資料庫遷移服務」工作時 遷移 MySQL 使用者資料。
This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services. This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.
In this course, you learn to analyze and choose the right database for your needs, to effectively develop applications on Google Cloud. You explore relational and NoSQL databases, dive into Cloud SQL, AlloyDB, and Spanner, and learn how to align database strengths with your application requirements, including those of generative AI. Gain hands-on experience configuring Vector Search and migrating applications to the cloud.
「Google Cloud 基礎知識:核心基礎架構」介紹了在使用 Google Cloud 時會遇到的重要概念和術語。本課程會透過影片和實作實驗室,介紹並比較 Google Cloud 的多種運算和儲存服務,同時提供重要的資源和政策管理工具。
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.
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.
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。
完成 透過 BigQuery 建構資料倉儲 技能徽章中階課程,即可證明您具備下列技能: 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表, 以及在 BigQuery 使用 JSON、陣列和結構體。
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。
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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.
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.
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.
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.
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.