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Wei-Ting Ho

Member since 2021

Diamond League

53333 points
Analyze patterns in conversational data with Conversational Insights Earned אוג 6, 2025 EDT
Conversational Insights Earned אוג 6, 2025 EDT
Build Production-Ready Conversational Agents Earned אוג 6, 2025 EDT
Leverage best practices for developing, operating, and securing production-grade Conversational Agents Earned אוג 6, 2025 EDT
Improve customer and agent satisfaction with Agent Assist Earned אוג 5, 2025 EDT
Agent Summarization (Custom) Earned אוג 5, 2025 EDT
Integrate Agent Assist with Telephony and Chatbot Systems Earned אוג 5, 2025 EDT
Introduction to Agent Assist and its GenAI Capabilities Earned אוג 5, 2025 EDT
Advanced Performance Measurement Earned יונ 23, 2025 EDT
Performance Measurement Earned יונ 23, 2025 EDT
Extend virtual agents with webhooks, tools, and Messenger integration Earned יונ 19, 2025 EDT
Conversational AI Voice and Chat Integrations Earned יונ 19, 2025 EDT
Extend Conversational Agents Functionality with Webhooks and Tools Earned יונ 18, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows Earned יונ 17, 2025 EDT
Virtual FAQ with data store agents Earned יונ 17, 2025 EDT
Incorporate Generative Features into Conversational Agent flows Earned יונ 16, 2025 EDT
Stateful Flows Earned יונ 16, 2025 EDT
Generative Playbooks Earned יונ 13, 2025 EDT
DFCX Virtual Agent Delivery Framework Earned מרץ 24, 2025 EDT
Text Prompt Engineering Techniques Earned מרץ 16, 2025 EDT
Deploy Google Agentspace Earned מרץ 11, 2025 EDT
Accelerate Knowledge Exchange with Google Agentspace Earned מרץ 11, 2025 EDT
Build generative virtual agents with API integrations Earned ינו 19, 2025 EST
Build deterministic Virtual Agent enhanced with data stores Earned ינו 19, 2025 EST
Google Cloud Fundamentals: Core Infrastructure Earned ינו 8, 2025 EST
Customer Engagement Suite with Google AI Architecture Earned נוב 18, 2024 EST
Intro to Conversational AI and Conversational AI Engagement Framework Earned אוק 30, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications Earned אפר 23, 2024 EDT
Custom Search with Embeddings in Vertex AI Earned אפר 11, 2024 EDT
Create Image Captioning Models - בעברית Earned אפר 11, 2024 EDT
Encoder-Decoder Architecture - בעברית Earned אפר 5, 2024 EDT
Preparing for Your Associate Cloud Engineer Journey Earned אפר 3, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps Earned מרץ 29, 2024 EDT
Building Gen AI Apps with Vertex AI: Prompting and Tuning Earned מרץ 27, 2024 EDT
Vector Search and Embeddings Earned מרץ 24, 2024 EDT
Implementing Generative AI with Vertex AI Earned מרץ 23, 2024 EDT
Generative AI for Business Leaders Earned פבר 12, 2024 EST
Introduction to CES and Conversational Agents Earned פבר 9, 2024 EST
Introduction to Image Generation - בעברית Earned דצמ 13, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud Earned דצמ 13, 2023 EST
Generative AI Fundamentals - בעברית Earned דצמ 12, 2023 EST
Introduction to Responsible AI - בעברית Earned דצמ 12, 2023 EST
Introduction to Generative AI - בעברית Earned דצמ 12, 2023 EST
Transformer Models and BERT Model - בעברית Earned יונ 16, 2023 EDT
Attention Mechanism - בעברית Earned יונ 16, 2023 EDT
Contact Center AI: Conversational Design Fundamentals Earned יונ 15, 2023 EDT
Introduction to Large Language Models - בעברית Earned יונ 14, 2023 EDT
Virtual Agent Development in Dialogflow CX for Citizen Devs Earned ספט 20, 2022 EDT
How Google Does Machine Learning Earned יונ 30, 2022 EDT
DEPRECATED Create Conversational AI Agents with Dialogflow CX Earned אפר 4, 2022 EDT
Cloud Engineering Earned נוב 5, 2021 EDT
Google Cloud Essentials Earned ספט 9, 2021 EDT
Prepare Data for ML APIs on Google Cloud Earned אוג 30, 2021 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned אוג 20, 2021 EDT
Customer Experiences with Contact Center AI Earned מאי 13, 2021 EDT

Complete the Analyze patterns in conversational data with Conversational Insights skill badge to demonstrate your proficiency in analysing customer conversations with Conversational Insights. After completing this challenge, you will be ready to deploy Conversation Insights to improve customer service performance, and create better customer experiences. 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 will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions. Please note Contact Center AI Insights were recently renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product name for Contact Center AI Insights.

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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents using best practices to create production-ready agents.

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Complete the Leverage best practices for developing, operating, and securing production-grade Conversational Agents skill badge to demonstrate your ability to implement a variety of best practices around development, deployment, and security. These will include: Using versions and environments, backing up with Git integration, leveraging test cases and CI/CD testing, tracking conversations with conversation history and logging, redacting data, and securing acceess to agent and webhook 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 develope…

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Complete the Improve customer and agent satisfaction with Agent Assist skill badge to demonstrate your proficiency in configuring basic conversational agents that can escalate actions to human agents, and configuring Agent Assist to help human agents with customer queries. You prove your knowledge in configuring Generators for summarization, classification and recommendation of tickets as well leverage tools such as Generative Knowledge Assist, to provide further context to human 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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In this course you will learn how Conversational AI Agent Assist can help distill complex customer interactions into concise and clear summaries. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.

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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the voice channel, as well as the options available for integration with other platforms in the Conversational AI ecosystem.

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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel.

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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 the fundamentals of the feedback loop process for Conversational Agent development and introduces the native capabilities within Conversational Agents that support it. You will also learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents.

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Complete the Extend agent functionality with Webhooks, Tools, and Integrations skill badge to demonstrate your ability to let conversational agents take actions. You will create a flow that calls a webhook and a playbook with a tool and combine them into a hybrid agent. You'll also prepare custom payload for rich content experiences in the Conversational Messenger. 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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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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Connect Conversational Agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.

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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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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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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows. Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.

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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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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 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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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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In this skill badge, you will demonstrate your ability to deploy Google Agentspace and set up data stores and actions. To learn these skills, we encourage you to take the course Accelerate Knowledge Exchange with Agentspace.

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Unite Google’s expertise in search and AI with Google Agentspace, an enterprise tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Google Agentspace assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds.

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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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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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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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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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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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בקורס הזה תלמדו איך ליצור מודל הוספת כיתוב לתמונה באמצעות למידה עמוקה (Deep Learning). אתם תלמדו על הרכיבים השונים במודל הוספת כיתוב לתמונה, כמו המקודד והמפענח, ואיך לאמן את המודל ולהעריך את הביצועים שלו. בסוף הקורס תוכלו ליצור מודלים להוספת כיתוב לתמונה ולהשתמש בהם כדי ליצור כיתובים לתמונות

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בקורס הזה לומדים בקצרה על ארכיטקטורת מקודד-מפענח, ארכיטקטורה עוצמתית ונפוצה ללמידת מכונה שמשתמשים בה במשימות של רצף לרצף, כמו תרגום אוטומטי, סיכום טקסט ומענה לשאלות. תלמדו על החלקים השונים בארכיטקטורת מקודד-מפענח, איך לאמן את המודלים האלה ואיך להשתמש בהם. בהדרכה המפורטת המשלימה בשיעור ה-Lab תקודדו ב-TensorFlow תרחיש שימוש פשוט בארכיטקטורת מקודד-מפענח: כתיבת שיר מאפס.

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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

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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 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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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.

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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 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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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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בקורס נלמד על מודלים של דיפוזיה, משפחת מודלים של למידת מכונה שיצרו הרבה ציפיות לאחרונה בתחום של יצירת תמונות. מודלים של דיפוזיה שואבים השראה מפיזיקה, וספציפית מתרמודינמיקה. בשנים האחרונות, מודלים של דיפוזיה הפכו לפופולריים גם בתחום המחקר וגם בתעשייה. מודלים של דיפוזיה עומדים מאחורי הרבה מהכלים והמודלים החדשניים ליצירת תמונות ב-Google Cloud. בקורס הזה נלמד על התיאוריה שמאחורי מודלים של דיפוזיה, ואיך לאמן ולפרוס אותם ב-Vertex AI.

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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

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רוצים לקבל תג מיומנות? אפשר להשלים את הקורסים Introduction to Generative AI, ‏Introduction to Large Language Models ו-Introduction to Responsible AI. מעבר של המבחן המסכם מוכיח שהבנתם את המושגים הבסיסיים בבינה מלאכותית גנרטיבית. 'תג מיומנות' הוא תג דיגיטלי ש-Google מנפיקה, שמוכיח שאתם מכירים את המוצרים והשירותים של Google Cloud. כדי לשתף את תג המיומנות אפשר להפוך את הפרופיל שלכם לגלוי לכולם ולהוסיף אותו לפרופיל שלכם ברשתות חברתיות.

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זהו קורס מבוא ממוקד שמטרתו להסביר מהי אתיקה של בינה מלאכותית, למה היא חשובה ואיך Google נוהגת לפי כללי האתיקה של הבינה המלאכותית במוצרים שלה. מוצגים בו גם 7 עקרונות ה-AI של Google.

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זהו קורס מבוא ממוקד שמטרתו להסביר מהי בינה מלאכותית גנרטיבית, איך משתמשים בה ובמה היא שונה משיטות מסורתיות של למידת מכונה. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.

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בקורס הזה נציג את הארכיטקטורה של טרנספורמרים ואת המודל של ייצוגים דו-כיווניים של מקודד מטרנספורמרים (BERT). תלמדו על החלקים השונים בארכיטקטורת הטרנספורמר, כמו מנגנון תשומת הלב, ועל התפקיד שלו בבניית מודל BERT. תלמדו גם על המשימות השונות שאפשר להשתמש ב-BERT כדי לבצע אותן, כמו סיווג טקסטים, מענה על שאלות והֶקֵּשׁ משפה טבעית. נדרשות כ-45 דקות כדי להשלים את הקורס הזה.

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בקורס נלמד על מנגנון תשומת הלב, שיטה טובה מאוד שמאפשרת לרשתות נוירונים להתמקד בחלקים ספציפיים ברצף הקלט. נלמד איך עובד העיקרון של תשומת הלב, ואיך אפשר להשתמש בו כדי לשפר את הביצועים במגוון משימות של למידת מכונה, כולל תרגום אוטומטי, סיכום טקסט ומענה לשאלות.

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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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זהו קורס מבוא ממוקד שבוחן מהם מודלים גדולים של שפה (LLM), איך משתמשים בהם בתרחישים שונים לדוגמה ואיך אפשר לשפר את הביצועים שלהם באמצעות כוונון של הנחיות. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.

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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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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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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.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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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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