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Fabiano Damasceno

Учасник із 2022

Spanner Foundations Earned лип. 18, 2026 EDT
Introduction to Gemini Enterprise Earned бер. 7, 2026 EST
Build Your First Agent with Agent Development Kit (ADK) Earned січ. 11, 2026 EST
Agent Fundamentals Earned січ. 11, 2026 EST
Model Armor: Securing AI Deployments Earned серп. 22, 2025 EDT
Gen AI Agents: Transform Your Organization Earned черв. 24, 2025 EDT
Gen AI Apps: Transform Your Work Earned черв. 23, 2025 EDT
Gen AI: Navigate the Landscape Earned черв. 22, 2025 EDT
Gen AI: Unlock Foundational Concepts Earned черв. 22, 2025 EDT
Gen AI: Beyond the Chatbot Earned черв. 22, 2025 EDT
Improve Agent Search findings on Gemini platform Earned черв. 3, 2025 EDT
Agent Search Analytics on Gemini platform Earned черв. 3, 2025 EDT
Agent Search UI configurations on Gemini platform Earned черв. 3, 2025 EDT
[DEPRECATED] Contact Center AI: Conversational Design Fundamentals Earned бер. 21, 2025 EDT
Exploring Data Transformation with Google Cloud Earned бер. 3, 2025 EST
[DEPRECATED] Conversation Design Fundamentals Earned лют. 24, 2025 EST
Digital Transformation with Google Cloud Earned лют. 24, 2025 EST
[DEPRECATED] Deploy Google Agentspace Earned лют. 11, 2025 EST
Accelerate Knowledge Exchange with Gemini Enterprise Earned лют. 11, 2025 EST
Принципи відповідального використання ШІ для розробників: інтерпретованість і прозорість Earned груд. 26, 2024 EST
Принципи відповідального використання ШІ для розробників: об’єктивність і упередженість Earned серп. 14, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned черв. 20, 2024 EDT
Vector Search and Embeddings Earned черв. 19, 2024 EDT
Introduction to Vertex AI Studio Earned черв. 2, 2024 EDT
Create Image Captioning Models Earned трав. 7, 2024 EDT
Transformer Models and BERT Model Earned квіт. 25, 2024 EDT
Encoder-Decoder Architecture Earned квіт. 15, 2024 EDT
Attention Mechanism Earned квіт. 12, 2024 EDT
Introduction to Image Generation Earned квіт. 11, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - Yкраїнська Earned квіт. 11, 2024 EDT
Prompt Design in Agent Platform Earned квіт. 11, 2024 EDT
Introduction to Responsible AI - Українська Earned квіт. 1, 2024 EDT
Introduction to Large Language Models - Українська Earned бер. 27, 2024 EDT
Introduction to Generative AI - Українська Earned бер. 26, 2024 EDT
Налаштування Cloud Load Balancing для Compute Engine Earned груд. 13, 2022 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned лист. 8, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals - українська Earned жовт. 16, 2022 EDT

This foundational course introduces learners to Google Cloud Spanner, the fully managed, mission-critical relational database. Designed primarily for application developers, cloud architects, and database administrators, this course covers the core tenets of Spanner: global consistency, relational schema design, and horizontal scalability. The curriculum is enriched with modern operational context, exploring how Spanner editions optimize costs, how the PostgreSQL interface broadens ecosystem compatibility, and how multi-model capabilities eliminate the need for complex data silos.

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This course introduces Gemini Enteprise, a powerful platform that brings together AI agents, enterprise search, Gemini Notebook, and intelligent data access to solve organizational challenges. Through real-world examples and hands-on exploration, learners will be able to connect Gemini Enterprise capabilities to real business needs, describe its architecture, and explain how it handles data access and privacy across roles. Explore other content in the Gemini Agent Ready (GEAR) program.

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Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK) in Gemini platform. In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior Explore other content in the Gemini Agent Ready (GEAR) program.

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This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior. Explore other content in the Gemini Agent Ready (GEAR) program.

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This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI apps. Explore other content in the Gemini Agent Ready (GEAR) program.

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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools. Explore other content in the Gemini Agent Ready (GEAR) program.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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This course covers techniques for boosting and filtering search results, as well as the implementation of meta tags for advanced search control.

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AI Applications provides built-in analytics for your Agent Search and Gemini. Learn what metrics are tracked and how to view them in this course.

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Initial deployment of Agent Search and Gemini takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience. In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Gemini.

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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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Cloud technology is a powerful asset, and when paired with data, it becomes a catalyst for innovation and enhanced customer experiences. Exploring Data Transformation with Google Cloud examines how organizations can leverage the cloud to make their data more accessible, actionable, and valuable. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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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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Digital transformation is a critical journey for modern organizations, and establishing a strong baseline in cloud computing is the first step toward driving meaningful innovation. Digital Transformation with Google Cloud introduces the core technologies and strategic frameworks that help organizations modernize their operations. This course explores fundamental cloud concepts, global network infrastructure, and the shared responsibility model to help leaders navigate their path to the cloud with confidence. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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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 Gemini Enterprise, a powerful 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 Gemini Enterprise 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. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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У цьому курсі розглядаються поняття інтерпретованості й прозорості штучного інтелекту, а також їх важливість для розробників. Ви дізнаєтеся про практичні методи й інструменти, які дають змогу досягти інтерпретованості й прозорості даних і моделей штучного інтелекту.

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Під час цього курсу ви зможете ознайомитися з концепціями відповідального підходу й принципами щодо штучного інтелекту. Ви дізнаєтеся про практичні методи виявлення об’єктивності й упередженості в роботі ШІ та технологій машинного навчання, а також ознайомитеся зі способами мінімізувати упередженість. У курсі розглядаються практичні методи й інструменти для впровадження відповідального підходу до ШІ за допомогою продуктів Google Cloud і інструментів із відкритим кодом.

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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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. Explore other content in the Gemini Agent Ready (GEAR) program.

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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images

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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.

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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Gemini Enterprise Agent Platform.

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Що більше штучний інтелект і машинне навчання використовуються в корпоративних середовищах, то нагальнішою стає потреба розробити принципи відповідального ставлення до них. Однак говорити про принципи відповідального використання штучного інтелекту легше, ніж застосовувати їх на практиці. Цей курс допоможе вам дізнатись, як запровадити відповідальну роботу зі штучним інтелектом у вашій організації. У цьому курсі ви дізнаєтеся про підхід Google Cloud до відповідального використання ШІ, а також отримаєте практичні поради й набудете досвіду, який допоможе вам розробити власний підхід до цього завдання.

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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке відповідальне використання штучного інтелекту, чому воно важливе і як компанія Google реалізує його у своїх продуктах. Крім того, у цьому курсі викладено 7 принципів Google щодо штучного інтелекту.

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У цьому ознайомлювальному курсі мікронавчання ви дізнаєтеся, що таке великі мовні моделі, де вони використовуються і як підвищити їх ефективність коригуванням запитів. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучного інтелекту.

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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.

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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.

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