Roberto de Souza Ribeiro Moraes Junior
Member since 2021
Build Real World AI Applications with Gemini and Imagen
Earned אפר 18, 2026 EDT
Introduction to AI Agents
Earned אפר 11, 2026 EDT
Develop Serverless Apps with Firebase
Earned אפר 8, 2026 EDT
Google DeepMind: 04 Discover The Transformer Architecture
Earned פבר 2, 2026 EST
Google DeepMind: 03 Design And Train Neural Networks
Earned פבר 2, 2026 EST
Google DeepMind: 02 Represent Your Language Data
Earned פבר 2, 2026 EST
Google DeepMind: 01 Build Your Own Small Language Model
Earned פבר 1, 2026 EST
Introduction to Security Principles in Cloud Computing
Earned דצמ 16, 2025 EST
Strategies for Cloud Security Risk Management
Earned דצמ 16, 2025 EST
Cloud Security Risks: Identify and Protect Against Threats
Earned דצמ 16, 2025 EST
Data Transformation in the Cloud
Earned דצמ 16, 2025 EST
The Power of Storytelling: How to Visualize Data in the Cloud
Earned דצמ 16, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned דצמ 16, 2025 EST
Data Management and Storage in the Cloud
Earned דצמ 11, 2025 EST
Introduction to Data Analytics in Google Cloud
Earned אוק 28, 2025 EDT
Data Management and Storage in the Cloud
Earned נוב 27, 2024 EST
Creating New BigQuery Datasets and Visualizing Insights
Earned אוק 23, 2024 EDT
הבנת העלויות ב-Google Cloud
Earned אוק 22, 2024 EDT
[Deprecated] Get Started with Looker
Earned אוק 21, 2024 EDT
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned ספט 11, 2024 EDT
The Power of Storytelling: How to Visualize Data in the Cloud
Earned ספט 11, 2024 EDT
Data Transformation in the Cloud
Earned ספט 11, 2024 EDT
Introduction to Data Analytics in Google Cloud
Earned ספט 10, 2024 EDT
Cloud Security Risks: Identify and Protect Against Threats
Earned יונ 27, 2024 EDT
Strategies for Cloud Security Risk Management
Earned יונ 27, 2024 EDT
Introduction to Security Principles in Cloud Computing
Earned יונ 27, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned יונ 27, 2024 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned יונ 27, 2024 EDT
Responsible AI for Developers: Fairness & Bias
Earned יונ 27, 2024 EDT
Vector Search and Embeddings
Earned יונ 26, 2024 EDT
Introduction to Generative AI Studio - בעברית
Earned יונ 26, 2024 EDT
Create Image Captioning Models - בעברית
Earned יונ 26, 2024 EDT
Transformer Models and BERT Model - בעברית
Earned יונ 26, 2024 EDT
Encoder-Decoder Architecture - בעברית
Earned יונ 26, 2024 EDT
Attention Mechanism - בעברית
Earned יונ 26, 2024 EDT
Introduction to Image Generation - בעברית
Earned יונ 26, 2024 EDT
[DEPRECATED] Gemini for Application Developers
Earned יונ 26, 2024 EDT
[DEPRECATED] Gemini for DevOps Engineers
Earned יונ 26, 2024 EDT
[DEPRECATED] Gemini for Network Engineers
Earned יונ 26, 2024 EDT
[DEPRECATED] Gemini for Data Scientists and Analysts
Earned יונ 26, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned יונ 25, 2024 EDT
Prompt Design in Agent Platform
Earned יונ 24, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned יונ 21, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned יונ 21, 2024 EDT
Introduction to Responsible AI - בעברית
Earned יונ 21, 2024 EDT
Introduction to Large Language Models - בעברית
Earned יונ 21, 2024 EDT
Introduction to Generative AI - בעברית
Earned יונ 21, 2024 EDT
Analyze Speech and Language with Google APIs
Earned יונ 20, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned יונ 12, 2024 EDT
[DEPRECATED] Gemini for end-to-end SDLC
Earned יונ 12, 2024 EDT
[DEPRECATED] Gemini for Security Engineers
Earned יונ 12, 2024 EDT
[DEPRECATED] Gemini for Cloud Architects
Earned יונ 12, 2024 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned אפר 5, 2024 EDT
Set Up a Google Cloud Network
Earned אפר 3, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned אפר 2, 2024 EDT
Derive Insights from BigQuery Data
Earned אפר 2, 2024 EDT
Building No-Code Apps with AppSheet: Foundations
Earned אפר 2, 2024 EDT
Google Cloud Data Analytics Essentials
Earned אפר 1, 2024 EDT
Build a Certification Study Guide: ACE Exam Prep
Earned פבר 5, 2024 EST
Google Cloud Fundamentals: Core Infrastructure - Locales
Earned דצמ 13, 2023 EST
Preparing for Your Associate Cloud Engineer Journey - Locales
Earned דצמ 7, 2023 EST
Elastic Google Cloud Infrastructure: Scaling and Automation - Locales
Earned דצמ 5, 2023 EST
Essential Google Cloud Infrastructure: Core Services - Locales
Earned דצמ 5, 2023 EST
Build Infrastructure with Terraform on Google Cloud
Earned יונ 16, 2023 EDT
Develop Your Google Cloud Network
Earned יונ 12, 2023 EDT
Deploy Kubernetes Applications on Google Cloud
Earned ינו 11, 2023 EST
BigQuery for Machine Learning
Earned יול 25, 2022 EDT
Baseline: Data, ML, AI
Earned יול 25, 2022 EDT
Baseline: Infrastructure
Earned יול 18, 2022 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned יונ 10, 2022 EDT
Automate Interactions with Contact Center AI
Earned יונ 1, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned מאי 31, 2022 EDT
Create ML Models with BigQuery ML
Earned מאי 30, 2022 EDT
Prepare Data for ML APIs on Google Cloud
Earned מאי 24, 2022 EDT
Build a Secure Google Cloud Network
Earned מאי 24, 2022 EDT
Set Up an App Dev Environment on Google Cloud
Earned מאי 23, 2022 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned מאי 23, 2022 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned ינו 9, 2022 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned ינו 9, 2022 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned דצמ 5, 2021 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned דצמ 1, 2021 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Earned נוב 12, 2021 EST
Google Cloud Essentials
Earned נוב 12, 2021 EST
Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Google Cloud Agent Platform. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.
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Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.
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In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.
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In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
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In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
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This is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.
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This is the second of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore widely-used cloud risk management frameworks, exploring security domains, compliance lifecycles, and industry standards such as HIPAA, NIST CSF, and SOC. You'll develop skills in risk identification, implementation of security controls, compliance evaluation, and data protection management. Additionally, you'll gain hands-on experience with Google Cloud and multi-cloud tools specific to risk and compliance. This course also incorporates job application and interview preparation techniques, offering a comprehensive foundation to understand and effectively navigate the complex landscape of cloud risk management.
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This is the third of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the principles of identity management and access control within a cloud environment, covering key elements like AAA (Authentication, Authorization, and Auditing), credential handling, and certificate management. You'll also explore essential topics in threat and vulnerability management, cloud-native principles, and data protection measures. Upon completing this course, you will have acquired the skills and knowledge necessary to secure cloud-based resources and safeguard sensitive organizational information. Additionally, you'll continue to engage with career resources and hone your interview techniques, preparing you for the next step in your professional journey.
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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.
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You’re over halfway through the program! This is the fourth course of the Google Cloud Data Analytics Certificate. Level up your data visualization skills by unlocking the secrets of transforming flat data into captivating stories that leap from the screen and onto the agenda of your key stakeholders. Happy learning!
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You made it! This is the fifth and final course of the Google Cloud Data Analytics Certificate. There’s no time like the present to start preparing for your job as a Cloud Data Analyst. Let's polish up that resume and refine those interview skills to allow you to show up with confidence for your interview!
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Hi again! This is the second course of the Google Cloud Data Analytics Certificate. Get cozy with the key components of data governance, normalized and star schemas, data catalogs, and data lakehouse architecture.
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Welcome learner! This is the first of five courses of the Google Cloud Data Analytics Certificate. Jump into the world of data analytics and cloud computing. Explore the data lifecycle in the cloud and gain a better understanding of the common tools used by data analysts.
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This is the second of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll explore how data is structured and organized. You’ll gain hands-on experience with the data lakehouse architecture and cloud components like BigQuery, Google Cloud Storage, and DataProc to efficiently store, analyze, and process large datasets.
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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources.
Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you.
After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
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המשימה הזו מתאימה במיוחד לבעלי תפקידים בתחומי הטכנולוגיה או הפיננסים, שאחראים לניהול של העלויות ב-Google Cloud. תלמדו איך להגדיר חשבון חיוב, איך לארגן משאבים ואיך לנהל הרשאות גישה לחיוב. בשיעורים המעשיים האלה תלמדו איך להציג את החשבונית, לנתח את נתוני החיוב באמצעות BigQuery או Google Sheets וליצור מרכזי בקרה לחיוב בהתאמה אישית באמצעות Data Studio.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.
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This is the fourth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll focus on developing skills in the five key stages of visualizing data in the cloud: storytelling, planning, exploring data, building visualizations, and sharing data with others. You’ll also gain experience using UI/UX skills to wireframe impactful, cloud-native visualizations and work with cloud-native data visualization tools to explore datasets, create reports, and build dashboards that drive decisions and foster collaboration.
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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.
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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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This is the third of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the principles of identity management and access control within a cloud environment, covering key elements like AAA (Authentication, Authorization, and Auditing), credential handling, and certificate management. You'll also explore essential topics in threat and vulnerability management, cloud-native principles, and data protection measures. Upon completing this course, you will have acquired the skills and knowledge necessary to secure cloud-based resources and safeguard sensitive organizational information. Additionally, you'll continue to engage with career resources and hone your interview techniques, preparing you for the next step in your professional journey.
Learn more
This is the second of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore widely-used cloud risk management frameworks, exploring security domains, compliance lifecycles, and industry standards such as HIPAA, NIST CSF, and SOC. You'll develop skills in risk identification, implementation of security controls, compliance evaluation, and data protection management. Additionally, you'll gain hands-on experience with Google Cloud and multi-cloud tools specific to risk and compliance. This course also incorporates job application and interview preparation techniques, offering a comprehensive foundation to understand and effectively navigate the complex landscape of cloud risk management.
Learn more
This is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.
Learn more
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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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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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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בקורס הזה נלמד על Generative AI Studio, מוצר ב-Vertex AI שעוזר ליצור אבות טיפוס למודלים של בינה מלאכותית גנרטיבית, כדי להשתמש בהם ולהתאים אותם לפי הצרכים שלכם. באמצעות הדגמה של המוצר עצמו, נלמד מהו Generative AI Studio, מהם הפיצ'רים והאפשרויות שלו, ואיך להשתמש בו. בסוף הקורס יהיה שיעור Lab מעשי לתרגול של מה שנלמד, ובוחן לבדיקת הידע.
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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 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 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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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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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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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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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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 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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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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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC).
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.
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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Data Studio by connecting to BigQuery data.
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In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users.
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Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.
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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.
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This course, Google Cloud Fundamentals: Core Infrastructure - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Fundamentals: Core Infrastructure.
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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This course, Preparing for Your Associate Cloud Engineer Journey - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Preparing for Your Associate Cloud Engineer Journey.
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, Elastic Google Cloud Infrastructure: Scaling and Automation - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Elastic Google Cloud Infrastructure: Scaling and Automation.
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
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This course, Essential Google Cloud Infrastructure: Core Services - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Essential Google Cloud Infrastructure: Core Services. This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like BigQuery, Cloud Speech API and Video Intelligence. Want extra help? 1-minute videos walk you through key concepts for each lab.
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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.
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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. 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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Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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 skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
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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 Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This third course covers cloud automation and management tools and building secure networks.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
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This course, Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Cloud Computing Fundamentals .The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
…
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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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