Jaimin Patel
成为会员时间:2021
钻石联赛
12015 积分
成为会员时间:2021
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
This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
In this course, you'll learn to develop generative agents that answer questions using websites, documents, or structured data. You will explore Vertex 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.
This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
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。
完成「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程,即可獲得技能徽章。通過最終測驗,就能展現您對生成式 AI 基本概念的掌握程度。 「技能徽章」是 Google Cloud 核發的數位徽章,用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中,向其他人分享您的成果。
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。
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。
Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents. This is an intermediate course, intended for learners with the following types of roles: Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows. Citizen developers: Creates new business applications fo…
本課程概要說明解碼器與編碼器的架構,這種強大且常見的機器學習架構適用於序列對序列的任務,例如機器翻譯、文字摘要和回答問題。您將認識編碼器與解碼器架構的主要元件,並瞭解如何訓練及提供這些模型。在對應的研究室逐步操作說明中,您將學習如何從頭開始使用 TensorFlow 寫程式,導入簡單的編碼器與解碼器架構來產生詩詞。
本課程說明如何使用深度學習來建立圖像說明生成模型。您將學習圖像說明生成模型的各個不同組成部分,例如編碼器和解碼器,以及如何訓練和評估模型。在本課程結束時,您將能建立自己的圖像說明生成模型,並使用模型產生圖像說明文字。
本課程將介紹擴散模型,這是一種機器學習模型,近期在圖像生成領域展現亮眼潛力。概念源自物理學,尤其深受熱力學影響。過去幾年來,在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中,擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論,並說明如何在 Vertex AI 上訓練和部署這些模型。
這堂課程將說明變換器架構,以及基於變換器的雙向編碼器表示技術 (BERT) 模型,同時帶您瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型。此外,也會介紹 BERT 適用的各種任務,像是文字分類、問題回答和自然語言推論。課程預計約 45 分鐘。
本課程將介紹注意力機制,說明這項強大技術如何讓類神經網路專注於輸入序列的特定部分。此外,也將解釋注意力的運作方式,以及如何使用注意力來提高各種機器學習任務的成效,包括機器翻譯、文字摘要和回答問題。
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。
只要修完「在 Google Cloud 設定應用程式開發環境」課程,就能獲得技能徽章。 在本課程中,您將學會如何使用以下技術的基本功能,建構和連結以儲存空間為中心的雲端基礎架構:Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。 「技能徽章」是 Google Cloud 核發的獨家數位徽章,用於表彰您相當熟悉 Google Cloud 產品與服務,並已通過測驗,能在互動式實作環境中應用相關知識。只要完成這個技能徽章課程和最終評量挑戰研究室,即可取得技能徽章並與親友分享成就。
這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務。這堂課結合了視訊講座、示範和實作研究室,可讓參加人員探索及部署解決方案元素,包括安全地建立互連網路、負載平衡、自動調度資源、基礎架構自動化,以及代管服務。
這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務,並將重點放在 Compute Engine。這堂課程結合了視訊講座、示範和實作研究室,可讓參加人員探索及部署解決方案元素,例如網路、系統和應用程式服務等基礎架構元件。另外,這堂課也會介紹如何部署實用的解決方案,包括客戶提供的加密金鑰、安全性和存取權管理機制、配額與帳單,以及資源監控功能。
這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務,尤其側重於 Compute Engine。這堂課程結合了視訊講座、示範和實作研究室,可讓參加人員探索及部署解決方案元素,例如網路、虛擬機器和應用程式服務等基礎架構元件。您會瞭解如何透過控制台和 Cloud Shell 使用 Google Cloud。另外,您也能瞭解雲端架構師的職責、基礎架構設計方法,以及具備虛擬私有雲 (VPC)、專案、網路、子網路、IP 位址、路徑和防火牆規則的虛擬網路設定。
「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。
In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Welcome to "CCAI Virtual Agent Development in Dialogflow ES for Software Developers", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn to use additional features of Dialogflow ES for your virtual agent, create a Firestore instance to store customer data, and implement cloud functions that access the data. With the ability to read and write customer data, learner’s virtual agents are conversationally dynamic and able to defer contact center volume from human agents. You'll be introduced to methods for testing your virtual agent and logs which can be useful for understanding issues that arise. Lastly, learn about connectivity protocols, APIs, and platforms for integrating your virtual agent with services already established for your business.
Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise. This is an intermediate course, intended for learners with the following type of role: Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
Welcome to "CCAI Operations and Implementation", the fourth course in the "Customer Experiences with Contact Center AI" series. In this course, learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale. In this course, you'll be introduced to Agent Assist and the technology it uses so you can delight your customers with the efficiencies and accuracy of services provided when customers require human agents, connectivity protocols, APIs, and platforms which you can use to create an integration between your virtual agent and the services already established for your business, Dialogflow's Environment Management tool for deployment of different versions of your virtual agent for various purposes, compliance measures and regulations you should be aware of when bringing your virtual agent to production, and you'll be given tips from virtua…
Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.
Learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You'll also learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale.