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Michael Verkruyse

Participante desde 2019

Liga Prata

26426 pontos
Customer Experience Agent Studio: Fundamentos Earned Sep 8, 2026 EDT
Build and Deploy Customer Experience Agents Earned Nov 6, 2025 EST
[CEPF L300 Course]: Cloud AI Earned Aug 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 Apr 12, 2024 EDT
Introdução ao Vertex AI Studio Earned Mar 27, 2024 EDT
Como criar modelos de legenda para imagens Earned Mar 27, 2024 EDT
Modelos de transformador e modelo de BERT Earned Mar 27, 2024 EDT
Mecanismo de atenção Earned Mar 26, 2024 EDT
Arquitetura de codificador-decodificador Earned Mar 26, 2024 EDT
Introdução à geração de imagens 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 tem como objetivo equipar designers e criadores de conversas com os conceitos e habilidades práticas para projetar, criar e testar agentes de experiência do cliente sofisticados, multiagentes e multimodais usando o 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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Neste curso, vamos conhecer o Vertex AI Studio, uma ferramenta para interagir com modelos de IA generativa, prototipar ideias comerciais e colocá-las em produção. Com a ajuda de um caso de uso imersivo, lições interessantes e um laboratório, você vai conhecer o ciclo de vida do comando à produção, além de usar o Vertex AI Studio para aplicativos multimodais do Gemini, design e engenharia de comandos e ajuste de modelos. O objetivo é permitir que você descubra todo o potencial da IA generativa nos seus projetos com o Vertex AI Studio.

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Neste curso, ensinamos a criar um modelo de legenda para imagens usando aprendizado profundo. Você vai aprender sobre os diferentes componentes de um modelo de legenda para imagens, como o codificador e decodificador, e de que forma treinar e avaliar seu modelo. Ao final deste curso, você será capaz de criar e usar seus próprios modelos de legenda para imagens.

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Este curso é uma introdução à arquitetura de transformador e ao modelo de Bidirectional Encoder Representations from Transformers (BERT, na sigla em inglês). Você vai aprender sobre os principais componentes da arquitetura de transformador, como o mecanismo de autoatenção, e como eles são usados para construir o modelo de BERT. Também vai conhecer as diferentes tarefas onde é possível usar o BERT, como classificação de texto, respostas a perguntas e inferência de linguagem natural. O curso leva aproximadamente 45 minutos.

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Este curso é uma introdução ao mecanismo de atenção, uma técnica avançada que permite que as redes neurais se concentrem em partes específicas de uma sequência de entrada. Você vai entender como a atenção funciona e como ela pode ser usada para melhorar o desempenho de várias tarefas de machine learning (como tradução automática, resumo de texto e resposta a perguntas).

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Este curso apresenta um resumo da arquitetura de codificador-decodificador, que é uma arquitetura de machine learning avançada e frequentemente usada para tarefas sequência para sequência (como tradução automática, resumo de textos e respostas a perguntas). Você vai conhecer os principais componentes da arquitetura de codificador-decodificador e aprender a treinar e disponibilizar esses modelos. No tutorial do laboratório relacionado, você vai codificar uma implementação simples da arquitetura de codificador-decodificador para geração de poesia desde a etapa inicial no TensorFlow.

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Neste curso, apresentamos os modelos de difusão, uma família de modelos de machine learning promissora no campo da geração de imagens. Os modelos de difusão são baseados na física, mais especificamente na termodinâmica. Nos últimos anos, eles se popularizaram no setor e nas pesquisas. Esses modelos servem de base para ferramentas e modelos avançados de geração de imagem no Google Cloud. Este curso é uma introdução à teoria dos modelos de difusão e como eles devem ser treinados e implantados na 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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