Extend CX Agents with Vertex AI Search data stores
Earned jul 4, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned may 30, 2024 EDT
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned may 30, 2024 EDT
Search with AI Applications
Earned may 30, 2024 EDT
Advanced Performance Measurement
Earned may 29, 2024 EDT
Advanced Webhook Concepts
Earned may 28, 2024 EDT
Generative Playbooks
Earned may 28, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned may 27, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned may 27, 2024 EDT
Vertex AI Search for Commerce
Earned may 27, 2024 EDT
Crea, entrena e implementa modelos de AA con Keras en Google Cloud
Earned may 22, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned may 21, 2024 EDT
Obtén estadísticas a partir de datos de BigQuery
Earned may 21, 2024 EDT
Crea un almacén de datos con BigQuery
Earned may 17, 2024 EDT
Understanding LookML in Looker
Earned may 16, 2024 EDT
Contact Center as a Service Implementation
Earned may 8, 2024 EDT
Building Complex End to End Self-Service Experiences in Dialogflow CX
Earned may 6, 2024 EDT
Developing Data Models with LookML
Earned abr 24, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned abr 24, 2024 EDT
Procesamiento de datos sin servidores con Dataflow: Fundamentos
Earned abr 17, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned abr 17, 2024 EDT
Crea un almacén de datos con BigQuery
Earned abr 11, 2024 EDT
Crea una malla de datos con Dataplex
Earned abr 10, 2024 EDT
Introducción a la generación de imágenes
Earned abr 5, 2024 EDT
Generative AI for Business Leaders
Earned abr 5, 2024 EDT
App Dev with Gemini
Earned mar 11, 2024 EDT
Getting Started with the Vertex AI Gemini API
Earned mar 8, 2024 EST
Multimodality with Gemini
Earned mar 8, 2024 EST
Custom Search with Embeddings in Vertex AI
Earned mar 8, 2024 EST
Búsqueda de vectores y embeddings
Earned mar 7, 2024 EST
Virtual Agent Development in Dialogflow ES for Software Devs
Earned mar 6, 2024 EST
CCAI Operations and Implementation
Earned mar 6, 2024 EST
Virtual Agent Development in Dialogflow CX for Software Devs
Earned mar 5, 2024 EST
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned mar 5, 2024 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned mar 5, 2024 EST
Contact Center AI: Conversational Design Fundamentals
Earned mar 1, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned mar 1, 2024 EST
Text Prompt Engineering Techniques
Earned feb 26, 2024 EST
Search with AI Applications
Earned feb 23, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned feb 23, 2024 EST
Generative AI Explorer : Vertex AI
Earned feb 22, 2024 EST
Introducción a Vertex AI Studio
Earned feb 21, 2024 EST
Generative AI Fundamentals
Earned feb 21, 2024 EST
IA responsable: Aplica los principios de la IA con Google Cloud
Earned feb 20, 2024 EST
Introducción a la IA responsable
Earned feb 20, 2024 EST
Introducción a los modelos de lenguaje grandes
Earned feb 20, 2024 EST
Introducción a la IA generativa
Earned feb 20, 2024 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned feb 20, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned feb 20, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud - Español
Earned ene 17, 2024 EST
Crea canalizaciones de datos por lotes en Google Cloud
Earned ene 8, 2024 EST
Crea data lakes y almacenes de datos en Google Cloud
Earned dic 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - Español
Earned dic 11, 2023 EST
This structured course is for developers interested in building intelligent agents using the Agent Development Kit (ADK). It combines hands-on experience, core concepts, and practical application, to provide a comprehensive guide to using ADK. You can also join our community of Google Cloud experts and peers to ask questions, collaborate on answers, and connect with the Googlers making the products you use every day.
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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
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En este curso, se muestra cómo usar modelos de IA/AA para tareas de IA generativa en BigQuery. A través de un caso de uso práctico relacionado con la administración de relaciones con clientes, conocerás el flujo de trabajo para solucionar un problema empresarial con modelos de Gemini. Para facilitar la comprensión, el curso también proporciona orientación paso a paso a través de soluciones de programación utilizando consultas en SQL y notebooks de Python.
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En este curso, aprenderás a usar el Kit de desarrollo de agentes de Google para crear sistemas complejos con multiagentes. Desarrollarás agentes equipados con herramientas y los conectarás con relaciones y flujos entre elementos superiores y secundarios para definir cómo interactúan. Ejecutarás tus agentes de forma local y los implementarás en Vertex AI Agent Engine para que operen como un flujo de agentes administrado. Agent Engine se encargará de las decisiones sobre infraestructura y el escalamiento de recursos.
Ten en cuenta que estos labs se basan en una versión preliminar de este producto. Puede haber un poco de retraso en estos labs mientras proporcionamos actualizaciones de mantenimiento.
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An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.
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En este curso, aprenderás a desarrollar una app con Flutter, el kit de herramientas de IU portátil de Google, y a integrar la app con Gemini, la familia de modelos de IA generativa de Google. También utilizarás Vertex AI Agent Builder, la plataforma de Google para crear y administrar agentes y aplicaciones basados en IA.
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This course provides an introduction to Looker Studio’s powerful features for data visualization and reporting. Learn to transform raw data into insightful reports by mastering various visualization options, connecting to diverse data sources, and implementing interactive controls such as filters. Explore data blending techniques to combine information from multiple sources and unlock deeper insights. Through hands-on exercises you'll gain the skills to create compelling, dynamic reports that effectively communicate data-driven stories.
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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.
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En este curso, se explora una solución de generación mejorada por recuperación (RAG) de BigQuery para mitigar las alucinaciones de la IA. Se presenta un flujo de trabajo de RAG que abarca la creación de embeddings, la búsqueda en un espacio vectorial y la generación de respuestas mejoradas. En el curso, se explican los motivos conceptuales de estos pasos y su implementación práctica con BigQuery. Al final del curso, los alumnos podrán crear una canalización de RAG utilizando BigQuery y modelos de IA generativa como Gemini y modelos de embedding para abordar sus propios casos de uso de alucinaciones de IA.
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Combina la experiencia en la búsqueda y la IA de Google con Gemini Enterprise, una herramienta potente diseñada para ayudar a los empleados a encontrar información específica en almacenes de documentos, correos electrónicos, chats, sistemas de tickets y otras fuentes de datos, todo desde una sola barra de búsqueda. El asistente de Gemini Enterprise también puede ayudarte a generar ideas, investigar, crear esquemas de documentos y realizar acciones como invitar a compañeros de trabajo a un evento de calendario para acelerar el trabajo de conocimiento y la colaboración de todo tipo.
(Ten en cuenta que Gemini Enterprise antes se llamaba Google Agentspace, por lo que puede haber referencias al nombre anterior del producto en este curso).
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This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.
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Obtén la insignia de habilidad intermedia Ingeniería de datos para crear modelos predictivos con BigQuery ML y demuestra tus capacidades para crear canalizaciones de transformación de datos en BigQuery con Dataprep de Trifacta; usar Cloud Storage, Dataflow y BigQuery para crear flujos de trabajo de extracción, transformación y carga (ETL), y crear modelos de aprendizaje automático con BigQuery ML.
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Obtén la insignia de habilidad intermedia Crea modelos de AA con BigQuery ML y demuestra tus habilidades para crear y evaluar modelos de aprendizaje automático con BigQuery ML para realizar predicciones de datos.
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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.
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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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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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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience 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.
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(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
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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.
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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.
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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 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.
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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.
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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
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En este curso, se explica cómo crear modelos de AA con TensorFlow y Keras, cómo mejorar la exactitud de los modelos de AA y cómo escribir modelos de AA para uso escalado.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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Completa la insignia de habilidad introductoria del curso Obtén estadísticas a partir de datos de BigQuery y demuestra tus habilidades para realizar las siguientes actividades: escribir consultas en SQL, consultar tablas públicas, cargar datos de muestra en BigQuery, solucionar problemas de errores de sintaxis habituales con el validador de consultas en BigQuery y crear informes en Looker Studio con la conexión a datos de BigQuery.
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Completa la insignia de habilidad intermedia Crea un almacén de datos con BigQuery para demostrar tus habilidades para realizar las siguientes actividades: unir datos para crear tablas nuevas, solucionar problemas de uniones, agregar datos a uniones, crear tablas particionadas por fecha, y trabajar con JSON, arrays y structs en BigQuery.
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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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An AI-driven Contact Center as a Service (CCaaS) solution that is built natively on Google Cloud. The Implementation course provides Partners with essential training about the delivery of key features and functionality. The course explores how to leverage your key understanding of the product into successful customer implementation engagements with tips, best practices, guides, and more.
Note: This product was previously called Contact Center AI (CCAI) Platform you may see references to that name still in the course, however the course is technically correct.
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This course will equip you with the tools to develop complex conversational experiences in Dialogflow CX capable of identifying the user intent and routing it to the right self service flow.
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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.
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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.
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Este curso corresponde a la 1ª parte de una serie de 3 cursos llamada Procesamiento de datos sin servidores con Dataflow. Para comenzar, en el primer curso haremos un repaso de qué es Apache Beam y cómo se relaciona con Dataflow. Luego, hablaremos sobre la visión de Apache Beam y los beneficios que ofrece su framework de portabilidad. Dicho framework hace posible que un desarrollador pueda usar su lenguaje de programación favorito con su backend de ejecución preferido. Después, le mostraremos cómo Dataflow le permite separar el procesamiento y el almacenamiento y, a la vez, ahorrar dinero. También le explicaremos cómo las herramientas de identidad, acceso y administración interactúan con sus canalizaciones de Dataflow. Por último, veremos cómo implementar el modelo de seguridad adecuado en Dataflow según su caso de uso.
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Learn how Gemini can revolutionize your ability to develop applications! This course helps developers go beyond the basics and learn how to integrate Gemini into their workflows.
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Completa la insignia de habilidad intermedia Crea un almacén de datos con BigQuery para demostrar tus habilidades para realizar las siguientes actividades: unir datos para crear tablas nuevas, solucionar problemas de uniones, agregar datos a uniones, crear tablas particionadas por fecha, y trabajar con JSON, arrays y structs en BigQuery.
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Completa el curso con insignia de habilidad introductoria Crea una malla de datos con Dataplex y demuestra tus habilidades para crear una malla de datos con Dataplex y facilitar la seguridad, la administración y el descubrimiento de datos en Google Cloud. Practicarás y pondrás a prueba tus habilidades para etiquetar recursos, asignar roles de IAM y evaluar la calidad de los datos en Dataplex.
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En este curso, se presenta una introducción a los modelos de difusión: una familia de modelos de aprendizaje automático que demostraron ser muy prometedores en el área de la generación de imágenes. Los modelos de difusión se inspiran en la física, específicamente, en la termodinámica. En los últimos años, los modelos de difusión se han vuelto populares tanto en investigaciones como en la industria. Los modelos de difusión respaldan muchos de los modelos de generación de imágenes y herramientas vanguardistas de Google Cloud. En este curso, se presenta la teoría detrás de los modelos de difusión y cómo entrenarlos y, luego, implementarlos en Vertex AI.
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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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Unlock the power of Google Cloud's cutting-edge Vertex AI Gemini API to craft innovative multimodal applications. This hands-on course delves into the integration of the Vertex AI SDK for Python, guiding you through the generation of sophisticated responses powered by the Gemini Pro and Gemini Pro Vision models. Get ready to build, deploy, and harness the transformative capabilities of multimodal AI within your own projects.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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Get hands-on with the Gemini Pro and Gemini Pro Vision models through our new labs. This course gives you a unique chance to explore these powerful AI tools while our training content is still in development. Learn to interact with the models using the Vertex AI Gemini API and cURL commands, and help us create the best possible learning experience around this technology.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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Delve into the power of multimodal AI with this project-based course using Gemini. Master essential techniques and build advanced applications. You will:
- Experiment with multimodal use cases to expand application possibilities
- Implement recommendation systems that combine suggestions with clear reasoning
- Design a powerful document search engine using multimodal RAG methods
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search.
You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
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En este curso, explorarás tecnologías, herramientas y aplicaciones de búsqueda potenciadas por IA. Aprende sobre las búsquedas semánticas utilizando embeddings de vectores, acerca de las búsquedas híbridas combinando enfoques semánticos y de palabras clave, y sobre la generación mejorada por recuperación (RAG) minimizando las alucinaciones como un agente de IA fundamentado. Adquiere experiencia práctica con Vector Search de Vertex AI para desarrollar tu motor de búsqueda inteligente.
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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.
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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…
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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.
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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.
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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…
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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.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
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(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.
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This content is deprecated. Please see the latest version of the course, here.
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En este curso, se presenta Vertex AI Studio, una herramienta para interactuar con modelos de IA generativa, crear prototipos de ideas de negocio y llevarlas a producción. A través de un caso de uso envolvente, lecciones atractivas y un lab práctico, explorarás el ciclo de vida desde la instrucción hasta el producto y aprenderás cómo aprovechar Vertex AI Studio para aplicaciones multimodales de Gemini, diseño de instrucciones, ingeniería de instrucciones y ajuste de modelos. El objetivo es permitirte desbloquear el potencial de la IA generativa en tus proyectos con Vertex AI Studio.
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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.
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A medida que aumenta el uso empresarial de la inteligencia artificial y el aprendizaje automático, también crece la importancia de implementarlo responsablemente. El desafío para muchas personas es que hablar sobre la IA responsable puede ser más fácil que aplicarla. Si te interesa aprender cómo poner en funcionamiento la IA responsable en tu organización, este curso es para ti.
En este curso, aprenderás cómo Google Cloud aplica estos principios en la actualidad, junto con las prácticas recomendadas y las lecciones aprendidas, para usarlos como marco de trabajo de modo que puedas crear tu propio enfoque de IA responsable.
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Este es un curso introductorio de microaprendizaje destinado a explicar qué es la IA responsable, por qué es importante y cómo la implementa Google en sus productos. También se presentan los 7 principios de la IA de Google.
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Este es un curso introductorio de microaprendizaje en el que se explora qué son los modelos de lenguaje grandes (LLM), sus casos de uso y cómo se puede utilizar el ajuste de instrucciones para mejorar el rendimiento de los LLM. También abarca las herramientas de Google para ayudarte a desarrollar tus propias aplicaciones de IA generativa.
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Este es un curso introductorio de microaprendizaje destinado a explicar qué es la IA generativa, cómo se utiliza y en qué se diferencia de los métodos de aprendizaje automático tradicionales. También abarca las herramientas de Google para ayudarte a desarrollar tus propias aplicaciones de IA generativa.
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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience 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.
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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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La incorporación del aprendizaje automático en las canalizaciones de datos aumenta la capacidad para extraer estadísticas de los datos. En este curso, veremos formas de incluir el aprendizaje automático en las canalizaciones de datos en Google Cloud. Para una personalización escasa o nula, en el curso se aborda AutoML. Para obtener más capacidades de aprendizaje automático a medida, el curso presenta Notebooks y BigQuery Machine Learning (BigQuery ML). Además, en este curso se aborda cómo llevar a producción soluciones de aprendizaje automático con Vertex AI.
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En este curso intermedio, aprenderás a diseñar, crear y optimizar canalizaciones de datos por lotes sólidas en Google Cloud. Más allá del manejo de datos fundamental, explorarás las transformaciones de datos a gran escala y la organización eficiente de flujos de trabajo, lo que es primordial para la inteligencia empresarial oportuna y los informes esenciales.
Obtén experiencia práctica con Dataflow para Apache Beam y Serverless for Apache Spark (Dataproc Serverless) para la implementación, y aborda consideraciones cruciales respecto de la calidad de los datos, la supervisión y las alertas para garantizar la confiabilidad de la canalización y la excelencia operativa. Se recomienda tener conocimientos básicos sobre almacenamiento de datos, ETL/ELT, SQL, Python y conceptos de Google Cloud.
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Si bien los enfoques tradicionales de usar data lakes y almacenes de datos pueden ser eficaces, tienen deficiencias, en particular en entornos empresariales grandes. En este curso, se presenta el concepto del data lakehouse y los productos de Google Cloud que se usan para crear uno. Una arquitectura de lakehouse usa fuentes de datos de estándares abiertos y combina las mejores funciones de los data lakes y los almacenes de datos, lo que aborda muchas de sus deficiencias.
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En este curso, aprenderás sobre los productos y servicios de macrodatos y aprendizaje automático de Google Cloud involucrados en el ciclo de vida de datos a IA. También explorarás los procesos, los desafíos y los beneficios de crear una canalización de macrodatos y modelos de aprendizaje automático con Vertex AI en Google Cloud.
Build intelligent agents with Agent Development Kit (ADK)
Earned oct 21, 2025 EDT
Data Lake Modernization on Google Cloud: Cloud Composer
Earned ago 14, 2025 EDT
Trabaja con modelos de Gemini en BigQuery
Earned ago 13, 2025 EDT
Implementa sistemas multiagente con el Kit de desarrollo de agentes (ADK) y Agent Engine
Earned ago 12, 2025 EDT
Empower Gen AI apps with tool use
Earned ago 12, 2025 EDT
Crea agentes basados en IA generativa con Vertex AI y Flutter
Earned ago 12, 2025 EDT
Looker Studio Essentials
Earned jul 28, 2025 EDT
Introduction to Looker
Earned jul 25, 2025 EDT
Crea embeddings, búsqueda de vectores y RAG con BigQuery
Earned jun 6, 2025 EDT
Acelera el intercambio de conocimientos con Gemini Enterprise
Earned jun 6, 2025 EDT
Orchestrating Gen AI Applications with LangChain
Earned jun 5, 2025 EDT
Ingeniería de datos para crear modelos predictivos con BigQuery ML
Earned feb 4, 2025 EST
Crea modelos de AA con BigQuery ML
Earned ene 16, 2025 EST
DFCX Virtual Agent Delivery Framework
Earned jul 4, 2024 EDT
Extend CX Agents with Vertex AI Search data stores
Earned jul 4, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned may 30, 2024 EDT
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned may 30, 2024 EDT
Search with AI Applications
Earned may 30, 2024 EDT
Advanced Performance Measurement
Earned may 29, 2024 EDT
Advanced Webhook Concepts
Earned may 28, 2024 EDT
Generative Playbooks
Earned may 28, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned may 27, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned may 27, 2024 EDT
Vertex AI Search for Commerce
Earned may 27, 2024 EDT
Crea, entrena e implementa modelos de AA con Keras en Google Cloud
Earned may 22, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned may 21, 2024 EDT
Obtén estadísticas a partir de datos de BigQuery
Earned may 21, 2024 EDT
Crea un almacén de datos con BigQuery
Earned may 17, 2024 EDT
Understanding LookML in Looker
Earned may 16, 2024 EDT
Contact Center as a Service Implementation
Earned may 8, 2024 EDT
Building Complex End to End Self-Service Experiences in Dialogflow CX
Earned may 6, 2024 EDT
Developing Data Models with LookML
Earned abr 24, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned abr 24, 2024 EDT
Procesamiento de datos sin servidores con Dataflow: Fundamentos
Earned abr 17, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned abr 17, 2024 EDT
Crea un almacén de datos con BigQuery
Earned abr 11, 2024 EDT
Crea una malla de datos con Dataplex
Earned abr 10, 2024 EDT
Introducción a la generación de imágenes
Earned abr 5, 2024 EDT
Generative AI for Business Leaders
Earned abr 5, 2024 EDT
App Dev with Gemini
Earned mar 11, 2024 EDT
Getting Started with the Vertex AI Gemini API
Earned mar 8, 2024 EST
Multimodality with Gemini
Earned mar 8, 2024 EST
Custom Search with Embeddings in Vertex AI
Earned mar 8, 2024 EST
Búsqueda de vectores y embeddings
Earned mar 7, 2024 EST
Virtual Agent Development in Dialogflow ES for Software Devs
Earned mar 6, 2024 EST
CCAI Operations and Implementation
Earned mar 6, 2024 EST
Virtual Agent Development in Dialogflow CX for Software Devs
Earned mar 5, 2024 EST
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned mar 5, 2024 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned mar 5, 2024 EST
Contact Center AI: Conversational Design Fundamentals
Earned mar 1, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned mar 1, 2024 EST
Text Prompt Engineering Techniques
Earned feb 26, 2024 EST
Search with AI Applications
Earned feb 23, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned feb 23, 2024 EST
Generative AI Explorer : Vertex AI
Earned feb 22, 2024 EST
Introducción a Vertex AI Studio
Earned feb 21, 2024 EST
Generative AI Fundamentals
Earned feb 21, 2024 EST
IA responsable: Aplica los principios de la IA con Google Cloud
Earned feb 20, 2024 EST
Introducción a la IA responsable
Earned feb 20, 2024 EST
Introducción a los modelos de lenguaje grandes
Earned feb 20, 2024 EST
Introducción a la IA generativa
Earned feb 20, 2024 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned feb 20, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned feb 20, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud - Español
Earned ene 17, 2024 EST
Crea canalizaciones de datos por lotes en Google Cloud
Earned ene 8, 2024 EST
Crea data lakes y almacenes de datos en Google Cloud
Earned dic 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - Español
Earned dic 11, 2023 EST