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Priyadarshan N. Mudholkar
Member since 2018
Gold League
14529 points
運用 BigQuery 建立嵌入項目、向量搜尋和 RAG
Earned Jan 6, 2026 EST
Generate and Edit Media in Agent Platform
Earned Dec 22, 2025 EST
Supervised Fine-tuning for Gemini
Earned Dec 4, 2025 EST
[DEPRECATED] Model evaluation on Vertex AI
Earned Dec 2, 2025 EST
Find, Explore and Deploy Model Garden Models
Earned Dec 2, 2025 EST
機器學習運作 (MLOps) 與 Vertex AI：模型評估
Earned Nov 30, 2025 EST
Build basic Conversational Agents with Playbooks and Flows
Earned Nov 25, 2025 EST
Extend CX Agents with Agent Search data stores
Earned Nov 24, 2025 EST
Incorporate Generative Features into Conversational Agent Flows
Earned Nov 20, 2025 EST
建立採用有狀態流程的對話式代理
Earned Nov 20, 2025 EST
[DEPRECATED] Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Nov 15, 2025 EST
Engineer Effective Prompts for Generative Models
Earned Nov 11, 2025 EST
Build search and recommendations applications with AI Applications
Earned Nov 8, 2025 EST
Introduction to AI Applications
Earned Nov 5, 2025 EST
Explore Google's Gen AI Models
Earned Oct 31, 2025 EDT
Generative Playbooks
Earned Sep 22, 2025 EDT
Introduction to Gemini for customer experience
Earned Sep 16, 2025 EDT
使用 Google Cloud 作業套件調度資源
Earned Sep 2, 2025 EDT
Google Cloud 的可靠性與安全性
Earned Aug 29, 2025 EDT
運用 Google Cloud 翻新基礎架構和應用程式
Earned Aug 28, 2025 EDT
運用 Google Cloud 人工智慧推動創新
Earned Aug 26, 2025 EDT
運用 Google Cloud 探索資料轉換功能
Earned Aug 22, 2025 EDT
透過 Google Cloud 進行數位轉型
Earned Aug 20, 2025 EDT
生成式 AI 代理：實現組織轉型
Earned Jul 21, 2025 EDT
生成式 AI 應用程式：徹底改變工作方式
Earned Jul 19, 2025 EDT
生成式 AI：掌握幕後技術與環境
Earned Jul 17, 2025 EDT
生成式 AI：瞭解基礎概念
Earned Jul 16, 2025 EDT
生成式 AI：不只是聊天機器人
Earned Jul 16, 2025 EDT
Scientific Data Processing
Earned Mar 1, 2019 EST
Machine Learning APIs
Earned Jan 11, 2019 EST
基本概念：資料、機器學習和 AI
Earned Oct 4, 2018 EDT
Google Cloud 必備知識
Earned Sep 29, 2018 EDT
這堂課程會說明 BigQuery 中的檢索增強生成 (RAG) 解決方案，協助您減少 AI 幻覺。當中介紹的 RAG 工作流程包含建立嵌入項目、搜尋向量空間，以及生成更符合需求的答案。另外，這堂課程會解釋這些步驟背後的概念與原因，以及實際運用 BigQuery 實作的方法。完成課程之後，學員將學會使用 BigQuery，以及 Gemini 和嵌入模型等生成式 AI 模型，建立 RAG pipeline 來處理自己的 AI 幻覺應用實例。
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This course dives into the world of media creation with Gemini Enterprise Agent Platform using Nano Banana and Veo. Learn to design text and image-based prompts to produce high-quality, consistent images, and captivating, cinematic video clips. You'll also learn to refine generated assets using core editing functions. Finally, this course guides you through multi-tool workflow implementations for creative control and consistency, empowering you to transform images into video clips and leverage Gemini for prompt writing assistance and feedback.
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With this course you will learn how to use different techniques to fine-tune Gemini. Model tuning is an effective way to customize large models like Gemini for your specific tasks. It's a key step to improve the model's quality and efficiency.
This course will give an overview of model tuning, describe the tuning options available for Gemini, help you determine when each tuning option should be used and how to perform tuning.
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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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Model Garden on Gemini platform is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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本課程針對評估生成式和預測式 AI 模型，向機器學習從業人員介紹相關的基礎工具、技術和最佳做法。模型評估是機器學習的重要領域，確保這類系統能在正式環境中提供可靠、準確且成效優異的結果。
學員將深入瞭解多種評估指標與方法，以及適用於不同模型類型和工作的應用方式。此外，也會特別介紹生成式 AI 模型帶來的獨特難題，並提供有效的應對策略。透過 Google Cloud Vertex AI 平台，學員將瞭解在模型挑選、最佳化和持續監控方面，該如何導入穩健的評估程序。
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Complete the Build basic Conversational Agents with Playbooks and Flows skill badge to demonstrate your proficiency in building virtual agents using traditional NLU and generative-based features.
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!
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In this course, you'll learn to develop AI agents that answer questions using websites, documents, or structured data. You will explore AI Applications and understand the advantages of data store agents, including their scalability and security.
You'll learn about different data store types and also discover how to connect data stores to agents and add personalization for enhanced responses.
Finally, you'll gain insights into common search configurations and troubleshooting techniques.
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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows.
Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.
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探索 Conversational Agents 中的流程、瞭解如何運用語言模型打造回應穩定的對話與語音體驗，並探討互動原因、意圖和實體等基本概念，以及如何運用這些概念建立對話式代理。
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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.
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Learn a variety of strategies and techniques to engineer effective prompts for generative models
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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores.
Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content.
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!
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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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Learn how to leverage Gemini multimodal capabilities to process and generate text, images, and audio and to integrate Gemini through APIs to perform tasks such as content creation and summarization.
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Explore Playbooks and their implementation of the ReAct pattern for building conversational agents. You will learn how to construct a Playbook, set up goals and instructions to build a chatbot in natural language, and learn to test and deploy your solution.
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This course explores the different products and capabilities of Gemini for customer experience, including CX Agent Studio, Agent Assist and CX Insights. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
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各種規模的機構都開始運用雲端的強大功能和靈活性，徹底改變營運方式。不過，有效管理及擴充雲端資源可能是相當複雜的工作。本課程將探討在雲端中的現代營運、可靠性和韌性的基礎概念，以及 Google Cloud 如何協助您達成這些目標。本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。
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組織將資料和應用程式遷移至雲端後，必須因應快速變化的安全性挑戰。本課程將探討雲端安全性的基礎知識、Google Cloud 融入安全考量設計的基礎架構價值，以及縱深防禦策略。此外，還會著重說明如何透過 AI 輔助作業和法規遵循工具，協助組織滿足嚴格的全球法規要求。
本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。
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許多傳統企業使用舊版系統和應用程式，無法滿足現今客戶的期望。企業主管經常需要在維護老舊的 IT 系統，以及投資新產品/服務之間做出選擇。本課程將探討這些挑戰，並提供解決方案，說明如何運用雲端技術克服難題。
本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。
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人工智慧 (AI) 和機器學習 (ML) 象徵著資訊技術的重大演進，正迅速改變各行各業。在「運用 Google Cloud 人工智慧推動創新」課程中，我們會探討組織如何運用 AI 和機器學習技術，翻轉業務流程。
本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。
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雲端技術是強大的資產，與資料搭配後，將成為創新和提升客戶體驗的催化劑。「運用 Google Cloud 探索資料轉換功能」課程將探討機構如何運用雲端，讓資料更易於存取、做為行動依據和更有價值。
這門課程是 Cloud Digital Leader 學習路徑的一部分，旨在協助個人在職務上成長，並打造企業的未來。
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數位轉型是現代組織必經的關鍵旅程，而建立穩固的雲端運算基礎，是跨出有意義創新的第一步。本課程「透過 Google Cloud 進行數位轉型」，將會介紹核心技術和策略框架，協助組織革新營運方式，並探討基本的雲端概念、全球網路基礎架構和共同責任模式，幫助主管在雲端之路上自信前行。本課程是 Cloud Digital Leader 學習路徑的一部分，旨在促進個人職能發展，並打造企業的未來。
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「生成式 AI 代理：實現組織轉型」是 Gen AI Leader 學習路徑的第五堂也是最後一堂課程。本課程將探討組織如何運用自訂生成式 AI 代理，解決特定的業務難題。您將動手練習建構基本的生成式 AI 代理，同時探索這類代理的各種元件，例如模型、推論迴圈和工具。
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「生成式 AI 應用程式：徹底改變工作方式」是 Generative AI Leader 學習路徑的第四門課程。本課程將介紹 Google 的生成式 AI 應用程式,例如 Gemini for Workspace 和NotebookLM,也會引導您瞭解各種概念,像是建立基準、檢索增強生成、建構有效的提示詞,以及打造自動化工作流程等。
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「生成式 AI：掌握幕後技術與環境」是 Gen AI Leader 學習路徑的第三門課程。生成式 AI 正在改變我們的工作方式，以及與周遭世界的互動模式。身為領導者，您要如何駕馭其強大的功能，創造實際的業務成果？在本課程中，您將認識建構生成式 AI 解決方案時的各個層面、Google Cloud 產品與服務，以及選擇解決方案時應考量的因素。
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生成式 AI：瞭解基礎概念是 Gen AI Leader 學習路徑的第二門課程。在本課程中，您將瞭解 AI、機器學習和生成式 AI 的差異，以及各種類型的資料如何協助生成式 AI 解決業務難題，進而掌握生成式 AI 的基礎概念。您還能深入瞭解 Google Cloud 因應基礎模型限制的策略，以及開發、部署安全且負責任的 AI 技術時面臨的主要挑戰。
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「生成式 AI：不只是聊天機器人」是 Gen AI Leader 學習路徑的第一門課程，沒有先修條件。本課程旨在帶領您超越對聊天機器人的基本認識，探索生成式 AI 能為貴組織帶來的真正潛力。您將瞭解基礎模型和提示工程等概念，這些都是發揮生成式 AI 威力的關鍵。本課程也會引導您思考重要事項，協助您為貴組織制定成功的生成式 AI 策略。
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題，但這些領域相當專業，就算想要入門 也難以取得教材或資料。幸好，Google Cloud 提供了此領域的多種服務，而且容易使用。 參加這堂入門課程，您就能踏出第一步， 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。
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在這堂入門課程，您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片， 針對實驗室涵蓋的概念提供更多背景資訊，協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課， 即使您尚未學習或不熟悉雲端知識， 也能從這堂課獲得實務經驗，並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器，還是在 Kubernetes Engine 或透過負載平衡執行應用程式， 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。
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