Configure and Maintain CCAIP as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCAIP.”
Manage Functions and Reporting with CCAI Platform provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCAI Platform.
This course teaches contact center agents about the core agent features and functionality in Contact Center AI Platform (CCAIP). CCAIP is a unified contact center platform that accelerates an organization's ability to leverage and deploy CCAI without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.
Unite Google’s expertise in search and AI with Google Agentspace, an enterprise tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Google Agentspace assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds.
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 course you will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions. Please note Contact Center AI Insights were recently renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product name for Contact Center AI Insights.
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.
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.
This course explores the different products and capabilities of Customer Engagement Suite (CES) and Conversational agents. 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.
Demonstrate the ability to create and deploy generative virtual agents with natural language using Vertex AI Agent Builder and augment responses by integrating Gemini responses with third party APIs and your own data stores You will use the following technologies and Google Cloud services: Vertex AI Agent Builder Gemini Cloud Functions
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.
In this course, you will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Conversational Agent self-service experiences. 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 will learn how Conversational AI Agent Assist can help distill complex customer interactions into concise and clear summaries. 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.
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
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 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.
Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the voice channel, as well as the options available for integration with other platforms in the Conversational AI ecosystem.
In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel.
This course explores the quality assurance best practices and the tools available in Conversational Agents to ensure production grade quality during Conversational Agent development, as well as the key tenets for the creation of a robust end to end deployment lifecycle. 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.
Discover flows in Conversational Agents and learn how to build deterministic chat and voice experiences with language models. Explore key concepts like drivers, intents, and entities, and how to use them to create conversational agents.
This course explores the fundamentals of the feedback loop process for Conversational Agent development and introduces the native capabilities within Conversational Agents that support it. 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, Virtual Agent, and CCAI Insights.
In this course, you will learn the important role that different types of webhooks play in Conversational Agents development, and how to effectively integrate them into your routine configuration of a Conversational Agent. 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.
This course explores the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel. 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.
This course explores the best practices, methods and tools to programmatically lead CCAI virtual agent delivery. It includes a high level overview of the end to end journey for building and deploying a virtual agent, as well as the core tenets to create a strong delivery culture. Additionally, this course covers the best practices for workflow management, defect tracking, release management and post-release support to ensure optimal virtual agent performance.
This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.
Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
Il corso Google Cloud Computing Foundations fornirà a chi ha poca o nessuna esperienza di cloud computing una panoramica dettagliata dei concetti relativi alle nozioni di base del cloud, ai big data e al machine learning, oltre che a dove e come Google Cloud si inserisce. Alla fine del corso, i partecipanti saranno in grado di descrivere i concetti relativi al cloud computing, ai big data e al machine learning e dimostrare delle competenze pratiche. Questo corso fa parte della serie di corsi Google Cloud Computing Foundations. I corsi dovrebbero essere completati nel seguente ordine: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Questo terzo corso illustra come creare reti protette e stru…
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.
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.
Dal momento che l'uso dell'intelligenza artificiale e del machine learning nelle aziende continua a crescere, cresce anche l'importanza di realizzarli in modo responsabile. Molti sono scoraggiati dal fatto che parlare di IA responsabile può essere più facile che metterla in pratica. Se vuoi imparare come operativizzare l'IA responsabile nella tua organizzazione, questo corso fa per te. In questo corso scoprirai come Google Cloud ci riesce attualmente, oltre alle best practice e alle lezioni apprese, per fungere da framework per costruire il tuo approccio all'IA responsabile.
Il corso Viaggio nell'AI generativa - Vertex AI è una raccolta di lab su come utilizzare l'AI generativa su Google Cloud. Nei lab imparerai a utilizzare i modelli nella famiglia di API Vertex AI PaLM, tra cui text-bison, chat-bison, e textembedding-gecko. Acquisirai inoltre competenze su progettazione di prompt, best practice e modalità di utilizzo per l'ideazione, oltre che per la classificazione, l'estrazione e il riassunto di testi e altro ancora. Imparerai anche come ottimizzare un foundation model utilizzando l'addestramento personalizzato di Vertex AI ed eseguendone il deployment in un endpoint Vertex AI.
Guadagna un badge delle competenze completando i corsi Introduction to Generative AI, Introduction to Large Language Models e Introduction to Responsible AI. Superando il quiz finale, dimostrerai la tua comprensione dei concetti fondamentali relativi all'IA generativa. Un badge delle competenze è un badge digitale rilasciato da Google Cloud come riconoscimento della tua conoscenza dei prodotti e dei servizi Google Cloud. Condividi il tuo badge delle competenze rendendo pubblico il tuo profilo e aggiungendolo al tuo profilo sui social media.
Questo corso illustra Generative AI Studio, un prodotto su Vertex AI che ti aiuta a prototipare e personalizzare i modelli di AI generativa in modo da poterne utilizzare le capacità nelle tue applicazioni. In questo corso imparerai cos'è Generative AI Studio, le sue funzionalità e opzioni e come utilizzarlo, esaminando le demo del prodotto. Alla fine, troverai un laboratorio pratico per mettere in pratica ciò che hai imparato e un quiz per testare le tue conoscenze.
Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'IA responsabile, perché è importante e in che modo Google implementa l'IA responsabile nei propri prodotti. Introduce anche i 7 principi dell'IA di Google.
Questo è un corso di microlearning di livello introduttivo che esplora cosa sono i modelli linguistici di grandi dimensioni (LLM), i casi d'uso in cui possono essere utilizzati e come è possibile utilizzare l'ottimizzazione dei prompt per migliorare le prestazioni dei modelli LLM. Descrive inoltre gli strumenti Google per aiutarti a sviluppare le tue app Gen AI.
Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'AI generativa, come viene utilizzata e in che modo differisce dai tradizionali metodi di machine learning. Descrive inoltre gli strumenti Google che possono aiutarti a sviluppare le tue app Gen AI.
Questo corso ti insegna come creare un modello per le didascalie delle immagini utilizzando il deep learning. Scoprirai i diversi componenti di un modello per le didascalie delle immagini, come l'encoder e il decoder, e imparerai ad addestrare e valutare il tuo modello. Alla fine di questo corso, sarai in grado di creare modelli personali per le didascalie delle immagini e utilizzarli per generare didascalie per le immagini.
Questo corso ti offre un riepilogo dell'architettura encoder-decoder, che è un'architettura di machine learning potente e diffusa per attività da sequenza a sequenza come traduzione automatica, riassunto del testo e risposta alle domande. Apprenderai i componenti principali dell'architettura encoder-decoder e come addestrare e fornire questi modelli. Nella procedura dettagliata del lab corrispondente, implementerai in TensorFlow dall'inizio un semplice codice dell'architettura encoder-decoder per la generazione di poesie da zero.
Questo corso introduce i modelli di diffusione, una famiglia di modelli di machine learning che recentemente si sono dimostrati promettenti nello spazio di generazione delle immagini. I modelli di diffusione traggono ispirazione dalla fisica, in particolare dalla termodinamica. Negli ultimi anni, i modelli di diffusione sono diventati popolari sia nella ricerca che nella produzione. I modelli di diffusione sono alla base di molti modelli e strumenti di generazione di immagini all'avanguardia su Google Cloud. Questo corso ti introduce alla teoria alla base dei modelli di diffusione e a come addestrarli ed eseguirne il deployment su Vertex AI.
Questo corso ti introduce all'architettura Transformer e al modello BERT (Bidirectional Encoder Representations from Transformers). Scopri i componenti principali dell'architettura Transformer, come il meccanismo di auto-attenzione, e come viene utilizzata per creare il modello BERT. Imparerai anche le diverse attività per le quali può essere utilizzato il modello BERT, come la classificazione del testo, la risposta alle domande e l'inferenza del linguaggio naturale. Si stima che il completamento di questo corso richieda circa 45 minuti.
Questo corso ti introdurrà al meccanismo di attenzione, una potente tecnica che consente alle reti neurali di concentrarsi su parti specifiche di una sequenza di input. Imparerai come funziona l'attenzione e come può essere utilizzata per migliorare le prestazioni di molte attività di machine learning, come la traduzione automatica, il compendio di testi e la risposta alle domande.
Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
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 "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.
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 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…
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.