Michael Verkruyse
Miembro desde 2019
Liga de Plata
26426 puntos
Customer Experience Agent Studio: Conceptos básicos
Earned sep 8, 2026 EDT
Build and Deploy Customer Experience Agents
Earned nov 6, 2025 EST
[CEPF L300 Course]: Cloud AI
Earned ago 3, 2024 EDT
[DEPRECATED] Conversation Design Fundamentals
Earned may 13, 2024 EDT
[DEPRECATED] Stateful Flows
Earned may 11, 2024 EDT
Advanced Webhook Concepts
Earned may 11, 2024 EDT
[DEPRECATED] Webhook fundamentals
Earned may 11, 2024 EDT
Building Complex End to End Self-Service Experiences in Dialogflow CX
Earned may 11, 2024 EDT
[DEPRECATED] Conversational Agents Quality Assurance and Deployment Lifecycle
Earned may 11, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned may 10, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned may 10, 2024 EDT
Implement Enterprise Design Patterns with CX Agent Studio
Earned may 10, 2024 EDT
Intro to CCAI and CCAI Engagement Framework
Earned may 8, 2024 EDT
CCAI Academy - Bot Building with Gen AI
Earned abr 12, 2024 EDT
Introducción a Vertex AI Studio
Earned mar 27, 2024 EDT
Creación de modelos de generación de subtítulos de imágenes
Earned mar 27, 2024 EDT
Modelos de transformadores y modelo BERT
Earned mar 27, 2024 EDT
Mecanismo de atención
Earned mar 26, 2024 EDT
Arquitectura de codificador-decodificador
Earned mar 26, 2024 EDT
Introducción a la generación de imágenes
Earned mar 26, 2024 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned mar 18, 2019 EDT
[DEPRECATED] Data Engineering
Earned mar 14, 2019 EDT
Este curso tiene como objetivo proporcionar a los diseñadores y creadores de conversaciones los conceptos y las habilidades prácticas para diseñar, crear y probar agentes de experiencia del cliente sofisticados, multiagente y multimodales con Customer Experience Agent Studio (CX Agent Studio).
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In this course you will discover the exciting new features and capabilities of Customer Experience Agent Studio (CX Agent Studio), design AI agents from the CLI using MCP servers, learn how to evaluate your agent's performance and implement the Quality Hill Climbing process. You will also find out how to set up your agent's memory to store, retrieve, and use information across conversation turns and implement callbacks for logging or authentication, configure guardrails to protect against malicious attempts and ensure aligned responses, and deploy the agent to various channels.
Additionally, you will explore the possible integrations between CX Agent Studio and CCaaS services and providers, including first party digital channel integrations with Google Telephony Platform (GTP), widgets and APIs, escalations to human agents through Google Cloud CCaaS and Gemini Enterprise for Customer Experience, and third party telephony and CCaaS integrations with providers such as Twillio or Salesfor…
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This Cloud AI course consists of a series of advanced-level labs designed to validate your proficiency in using Google Cloud's AI and ML services. Each lab presents a set of required tasks that you must complete with minimal assistance.
You must score 80% or higher for each lab to complete this course, and fulfill your CEPF L300 Cloud AI requirement.
Course Status: All required labs for this course are now released. You must use the latest version of the course to access these labs and ensure your progress is tracked correctly.
If a green upgrade banner appears at the top of the page, follow the prompts to upgrade before continuing. If no banner is shown, you are already on the latest version.
Required Labs: You only need to complete the labs marked as 'Required' to complete the course. Optional labs have no tag next to their titles; while recommended, they are not required.
L300 Accreditation: Full CEPF L300 accreditation for this specialization requires completion of all required…
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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.
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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.
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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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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.
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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 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.
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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 course explores using enterprise design patterns to build scalable, reliable, and secure agents within CX Agent Studio. Additionally, it covers navigating the complete development lifecycle by deploying multi-layered application security and locking down cloud infrastructure perimeters. It details the core pillars of multi-turn session persistence and real-time audio supervision to facilitate safe, continuous conversational experiences.
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This is a introductory course to all solutions in the Contact Centre AI (CCAI) portfolio and the Generative AI features that are poised to transform them. The course also explores the CCAI go to market and engagement model, the business case around CCAI, as well as the use cases and user personas addressed by the solution.
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The objective of this course is to upsklill experienced conversational AI practitioners on how to deliver Dialogflow Bots with new Gen AI capabilities
Brought to you by the GCC Tech Specialization Team (gcc-enablement-tech@). Share your request/feedback on go/learningpacks-feedback!
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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 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 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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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 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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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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