Evaluate Gen AI model and agent performance
Earned ago 27, 2025 EDT
Model evaluation on Vertex AI
Earned ago 26, 2025 EDT
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned ago 21, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned ago 19, 2025 EDT
Implement RAG with Vertex AI
Earned ago 17, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned ago 17, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned ago 16, 2025 EDT
Build Gen AI solutions using Model Garden models and APIs
Earned ago 15, 2025 EDT
Edit images with Imagen
Earned ago 13, 2025 EDT
Generate and Edit Media with Imagen, Gemini, and Veo
Earned ago 12, 2025 EDT
Implement Hybrid Search
Earned ago 12, 2025 EDT
Crea embeddings, búsqueda de vectores y RAG con BigQuery
Earned ago 12, 2025 EDT
Explore Google's Gen AI Models
Earned ago 12, 2025 EDT
Engineer Effective Prompts for Generative Models
Earned ago 6, 2025 EDT
Empower Gen AI apps with tool use
Earned ago 6, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned jul 25, 2025 EDT
Virtual FAQ with data store agents
Earned jun 17, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows
Earned jun 16, 2025 EDT
Generative Playbooks
Earned jun 16, 2025 EDT
Build deterministic Virtual Agent enhanced with data stores
Earned ene 17, 2025 EST
Build generative virtual agents with API integrations
Earned ene 17, 2025 EST
Customer Engagement Suite with Google AI Architecture
Earned oct 21, 2024 EDT
Intro to Conversational AI and Conversational AI Engagement Framework
Earned oct 21, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework
Earned ago 3, 2024 EDT
Operaciones de aprendizaje automático (MLOps) con Vertex AI: Administra atributos
Earned jun 7, 2024 EDT
Operaciones de aprendizaje automático (MLOps): Primeros pasos
Earned jun 6, 2024 EDT
Introduction to CES and Conversational Agents
Earned jun 6, 2024 EDT
Ingeniería de atributos
Earned jun 3, 2024 EDT
Crea, entrena e implementa modelos de AA con Keras en Google Cloud
Earned may 29, 2024 EDT
Launching into Machine Learning - Español
Earned may 28, 2024 EDT
Introducción a Vertex AI Studio
Earned may 24, 2024 EDT
Generative AI for Business Leaders
Earned may 24, 2024 EDT
Introducción a la IA y el aprendizaje automático en Google Cloud
Earned may 24, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned may 8, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned may 8, 2024 EDT
Búsqueda de vectores y embeddings
Earned may 7, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned feb 1, 2024 EST
Customer Experiences with Contact Center AI
Earned ene 30, 2024 EST
Text Prompt Engineering Techniques
Earned ene 25, 2024 EST
Generative AI Explorer : Vertex AI
Earned ene 24, 2024 EST
Introducción a Vertex AI Studio
Earned ene 19, 2024 EST
Introducción a la generación de imágenes
Earned ene 19, 2024 EST
Creación de modelos de generación de subtítulos de imágenes
Earned ene 18, 2024 EST
Arquitectura de codificador-decodificador
Earned ene 18, 2024 EST
Modelos de transformadores y modelo BERT
Earned ene 18, 2024 EST
Mecanismo de atención
Earned ene 18, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned ene 11, 2024 EST
Conversational AI on Vertex AI and Dialogflow CX
Earned ene 9, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned ene 1, 2024 EST
Implementing Generative AI with Vertex AI
Earned dic 9, 2023 EST
IA responsable: Aplica los principios de la IA con Google Cloud
Earned dic 4, 2023 EST
Generative AI Fundamentals - Español
Earned dic 3, 2023 EST
Introducción a la IA responsable
Earned dic 3, 2023 EST
Introducción a los modelos de lenguaje grandes
Earned dic 3, 2023 EST
CCAI Operations and Implementation
Earned jun 16, 2023 EDT
Virtual Agent Development in Dialogflow CX for Software Devs
Earned jun 15, 2023 EDT
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned jun 14, 2023 EDT
Introducción a la IA generativa
Earned jun 12, 2023 EDT
Contact Center AI: Conversational Design Fundamentals
Earned jun 12, 2023 EDT
DEPRECATED Create Conversational AI Agents with Dialogflow CX
Earned jun 7, 2023 EDT
Complete the Evaluate Gen AI model and agent performance skill badge to demonstrate your ability to use the Gen AI evaluation service. You will evaluate models to select the best model for a given task, compare models against each other and evaluate the performance of agents.
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 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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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.
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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.
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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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Model Garden 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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Model tuning is an effective way to customize large models to your tasks. It's a key step to improve the model's quality and efficiency. Model tuning provides benefits such as higher quality results for your specific tasks and increased model robustness. You learn some of the tuning options available in Vertex AI and when to use them.
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Complete the Develop solutions using Model Garden APIs skill badge to demonstrate your ability to use Vertex AI Model Garden features when building gen AI solutions. You will use partner APIs such as Anthropic Claude ands Meta Llama, deploy and programatically access foundation models like Gemma and Stable Diffusion XL and access Vertex AI Endpoints.
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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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
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!
Más información
Generate engaging media with Google's foundation models for media. Create new images with Imagen, or edit your existing photos by adding details or outpainting to create a wider view. Replace backgrounds to put your products in new scenes. And learn the basics of generating videos with Veo!
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Learn how to create Hybrid Search applications using Vertex AI Vertex Search to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.
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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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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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Learn a variety of strategies and techniques to engineer effective prompts for generative models
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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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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email.
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 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.
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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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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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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
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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
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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.
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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.
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Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.
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En este curso, se presentan a los participantes las herramientas y prácticas recomendadas de MLOps para implementar, evaluar, supervisar y operar sistemas de AA de producción en Google Cloud. Las MLOps son una disciplina enfocada en la implementación, prueba, supervisión y automatización de sistemas de AA en producción.
Los estudiantes obtendrán experiencia práctica con la transferencia de transmisión de Vertex AI Feature Store en la capa de SDK.
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En este curso, se presentan a los participantes las herramientas y prácticas recomendadas de MLOps para implementar, evaluar, supervisar y operar sistemas de AA de producción en Google Cloud. Las MLOps son una disciplina enfocada en la implementación, prueba, supervisión y automatización de sistemas de AA en producción. Los ingenieros profesionales de aprendizaje automático usan herramientas para mejorar y evaluar continuamente los modelos implementados. Trabajan con científicos de datos (o pueden serlo) que desarrollan modelos para ofrecer velocidad y rigor en la implementación de modelos con el mejor rendimiento.
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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.
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En este curso, se exploran los beneficios de utilizar Vertex AI Feature Store, cómo mejorar la exactitud de los modelos de AA y cómo descubrir cuáles columnas de datos producen los atributos más útiles. El curso también incluye contenido y labs sobre la ingeniería de atributos en los que se usan BigQuery ML, Keras y TensorFlow.
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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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El curso comienza con un debate sobre los datos: cómo mejorar su calidad y cómo realizar análisis exploratorios de ellos. Describimos Vertex AI AutoML y cómo crear, entrenar e implementar un modelo de AA sin escribir una sola línea de código. Conocerás los beneficios de BigQuery ML. Luego, se analiza cómo optimizar un modelo de aprendizaje automático (AA) y cómo la generalización y el muestreo pueden ayudar a evaluar la calidad de los modelos de AA para el entrenamiento personalizado.
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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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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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En este curso, se presentan las ofertas de aprendizaje automático (AA) en Google Cloud que compilan proyectos de IA predictiva y generativa. También se exploran las tecnologías, los productos y las herramientas disponibles durante el ciclo de vida desde los datos hasta la IA, que engloban los fundamentos, el desarrollo y las soluciones de IA. El objetivo es ayudar a científicos de datos, ingenieros de AA y desarrolladores de IA a mejorar sus habilidades y conocimientos a través de experiencias de aprendizaje atractivas y ejercicios prácticos.
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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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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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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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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.
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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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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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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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En este curso, se te enseña a crear un modelo de generación de leyendas de imágenes con el aprendizaje profundo. Aprenderás sobre los distintos componentes de los modelos de generación de leyendas de imágenes, como el codificador y el decodificador, y cómo entrenar y evaluar tu modelo. Al final del curso, podrás crear tus propios modelos y usarlos para generar leyendas de imágenes.
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En este curso, se brinda un resumen de la arquitectura de codificador-decodificador, una arquitectura de aprendizaje automático importante y potente para realizar tareas de secuencia por secuencia, como las de traducción automática, resúmenes de texto y respuestas a preguntas. Aprenderás sobre los componentes principales de la arquitectura de codificador-decodificador y cómo entrenar y entregar estos modelos. En la explicación del lab, programarás una implementación sencilla de la arquitectura de codificador-decodificador en TensorFlow para generar poemas desde un comienzo.
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En este curso, se presentan la arquitectura de transformadores y el modelo de Bidirectional Encoder Representations from Transformers (BERT). Aprenderás sobre los componentes principales de la arquitectura de transformadores, como el mecanismo de autoatención, y cómo se usa para crear el modelo BERT. También aprenderás sobre las diferentes tareas para las que puede usarse BERT, como la clasificación de texto, la respuesta de preguntas y la inferencia de lenguaje natural. Tardarás aproximadamente 45 minutos en completar este curso.
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Este curso es una introducción al mecanismo de atención, una potente técnica que permite a las redes neuronales enfocarse en partes específicas de una secuencia de entrada. Sabrás cómo funciona la atención y cómo puede utilizarse para mejorar el rendimiento de diversas tareas de aprendizaje automático, como la traducción automática, el resumen de textos y la respuesta a preguntas.
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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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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.
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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 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.
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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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Completa los cursos Introduction to Generative AI, Introduction to Large Language Models e Introduction to Responsible AI para obtener una insignia de habilidad. Aprueba el cuestionario final para demostrar que entiendes los conceptos básicos sobre la IA generativa.
Una insignia de habilidad es una insignia digital que emite Google Cloud en reconocimiento de tu dominio de los productos y servicios de la plataforma. Para compartir tu insignia de habilidad, establece tu perfil como público y agrega la insignia a tu perfil de redes sociales.
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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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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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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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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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Earn a skill badge by completing the Create Conversational AI Agents with Dialogflow CX quest, where you will learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR 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 this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
Evaluate Gen AI model and agent performance
Earned ago 27, 2025 EDT
Model evaluation on Vertex AI
Earned ago 26, 2025 EDT
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned ago 21, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned ago 19, 2025 EDT
Implement RAG with Vertex AI
Earned ago 17, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned ago 17, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned ago 16, 2025 EDT
Build Gen AI solutions using Model Garden models and APIs
Earned ago 15, 2025 EDT
Edit images with Imagen
Earned ago 13, 2025 EDT
Generate and Edit Media with Imagen, Gemini, and Veo
Earned ago 12, 2025 EDT
Implement Hybrid Search
Earned ago 12, 2025 EDT
Crea embeddings, búsqueda de vectores y RAG con BigQuery
Earned ago 12, 2025 EDT
Explore Google's Gen AI Models
Earned ago 12, 2025 EDT
Engineer Effective Prompts for Generative Models
Earned ago 6, 2025 EDT
Empower Gen AI apps with tool use
Earned ago 6, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned jul 25, 2025 EDT
Virtual FAQ with data store agents
Earned jun 17, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows
Earned jun 16, 2025 EDT
Generative Playbooks
Earned jun 16, 2025 EDT
Build deterministic Virtual Agent enhanced with data stores
Earned ene 17, 2025 EST
Build generative virtual agents with API integrations
Earned ene 17, 2025 EST
Customer Engagement Suite with Google AI Architecture
Earned oct 21, 2024 EDT
Intro to Conversational AI and Conversational AI Engagement Framework
Earned oct 21, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework
Earned ago 3, 2024 EDT
Operaciones de aprendizaje automático (MLOps) con Vertex AI: Administra atributos
Earned jun 7, 2024 EDT
Operaciones de aprendizaje automático (MLOps): Primeros pasos
Earned jun 6, 2024 EDT
Introduction to CES and Conversational Agents
Earned jun 6, 2024 EDT
Ingeniería de atributos
Earned jun 3, 2024 EDT
Crea, entrena e implementa modelos de AA con Keras en Google Cloud
Earned may 29, 2024 EDT
Launching into Machine Learning - Español
Earned may 28, 2024 EDT
Introducción a Vertex AI Studio
Earned may 24, 2024 EDT
Generative AI for Business Leaders
Earned may 24, 2024 EDT
Introducción a la IA y el aprendizaje automático en Google Cloud
Earned may 24, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned may 8, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned may 8, 2024 EDT
Búsqueda de vectores y embeddings
Earned may 7, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned feb 1, 2024 EST
Customer Experiences with Contact Center AI
Earned ene 30, 2024 EST
Text Prompt Engineering Techniques
Earned ene 25, 2024 EST
Generative AI Explorer : Vertex AI
Earned ene 24, 2024 EST
Introducción a Vertex AI Studio
Earned ene 19, 2024 EST
Introducción a la generación de imágenes
Earned ene 19, 2024 EST
Creación de modelos de generación de subtítulos de imágenes
Earned ene 18, 2024 EST
Arquitectura de codificador-decodificador
Earned ene 18, 2024 EST
Modelos de transformadores y modelo BERT
Earned ene 18, 2024 EST
Mecanismo de atención
Earned ene 18, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned ene 11, 2024 EST
Conversational AI on Vertex AI and Dialogflow CX
Earned ene 9, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned ene 1, 2024 EST
Implementing Generative AI with Vertex AI
Earned dic 9, 2023 EST
IA responsable: Aplica los principios de la IA con Google Cloud
Earned dic 4, 2023 EST
Generative AI Fundamentals - Español
Earned dic 3, 2023 EST
Introducción a la IA responsable
Earned dic 3, 2023 EST
Introducción a los modelos de lenguaje grandes
Earned dic 3, 2023 EST
CCAI Operations and Implementation
Earned jun 16, 2023 EDT
Virtual Agent Development in Dialogflow CX for Software Devs
Earned jun 15, 2023 EDT
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned jun 14, 2023 EDT
Introducción a la IA generativa
Earned jun 12, 2023 EDT
Contact Center AI: Conversational Design Fundamentals
Earned jun 12, 2023 EDT
DEPRECATED Create Conversational AI Agents with Dialogflow CX
Earned jun 7, 2023 EDT