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Apply your skills in Google Cloud console

Akhmad Khudri

Member since 2025

Diamond League

41757 points
Service Orchestration and Choreography on Google Cloud Earned דצמ 30, 2025 EST
Developing Applications with Google Cloud: Foundations Earned דצמ 28, 2025 EST
Google Cloud Fundamentals: Core Infrastructure Earned דצמ 23, 2025 EST
AI Infrastructure: Deployment Types Earned דצמ 17, 2025 EST
AI Infrastructure: Networking Techniques Earned דצמ 17, 2025 EST
Conversational AI on Vertex AI and Dialogflow CX Earned דצמ 16, 2025 EST
Gemini for Security Engineers Earned דצמ 16, 2025 EST
Gemini for Cloud Architects Earned דצמ 16, 2025 EST
AI Infrastructure: Storage Options Earned דצמ 16, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned דצמ 14, 2025 EST
Model Armor: Securing AI Deployments Earned דצמ 14, 2025 EST
Introduction to Security in the World of AI Earned דצמ 14, 2025 EST
Essential Google Cloud Infrastructure: Foundation Earned דצמ 14, 2025 EST
Gen AI Apps: Transform Your Work Earned דצמ 12, 2025 EST
Gen AI: Navigate the Landscape Earned דצמ 12, 2025 EST
Gen AI: Unlock Foundational Concepts Earned דצמ 12, 2025 EST
Gen AI: Beyond the Chatbot Earned דצמ 12, 2025 EST
AI Infrastructure: Cloud TPUs Earned דצמ 10, 2025 EST
AI Infrastructure: Cloud GPUs Earned דצמ 10, 2025 EST
AI Infrastructure: Introduction to AI Hypercomputer Earned דצמ 10, 2025 EST
Protect Cloud Traffic with Chrome Enterprise Premium Security Earned דצמ 10, 2025 EST
Use Machine Learning APIs on Google Cloud Earned דצמ 9, 2025 EST
Get Started with Google Workspace Tools Earned דצמ 8, 2025 EST
Deploy and Scale AI Models with Cloud Run Earned דצמ 7, 2025 EST
Configure Gemini Code Assist for Organizations Earned דצמ 7, 2025 EST
Accelerate App Development with Gemini CLI Earned דצמ 7, 2025 EST
Streamline App Development with Gemini Code Assist Earned דצמ 7, 2025 EST
Responsible AI for Developers: Interpretability & Transparency Earned דצמ 6, 2025 EST
Responsible AI for Developers: Fairness & Bias Earned דצמ 6, 2025 EST
Responsible AI for Developers: Privacy & Safety Earned דצמ 6, 2025 EST
Vector Search and Embeddings Earned דצמ 6, 2025 EST
Machine Learning Operations (MLOps) for Generative AI Earned דצמ 6, 2025 EST
Introduction to Generative AI Studio - בעברית Earned דצמ 6, 2025 EST
Create Image Captioning Models - בעברית Earned דצמ 6, 2025 EST
Transformer Models and BERT Model - בעברית Earned דצמ 6, 2025 EST
Encoder-Decoder Architecture - בעברית Earned דצמ 6, 2025 EST
Attention Mechanism - בעברית Earned דצמ 6, 2025 EST
Introduction to Image Generation - בעברית Earned דצמ 6, 2025 EST
Build Generative AI Agents with Vertex AI and Flutter Earned דצמ 5, 2025 EST
Website Modernization with Generative AI on Google Cloud Earned דצמ 4, 2025 EST
Create Generative AI Apps on Google Cloud Earned דצמ 4, 2025 EST
The Power of Storytelling: How to Visualize Data in the Cloud Earned דצמ 3, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job Earned דצמ 3, 2025 EST
Data Transformation in the Cloud Earned דצמ 3, 2025 EST
Trust and Security with Google Cloud Earned דצמ 3, 2025 EST
Infrastructure and Application Modernization with Google Cloud - בעברית Earned דצמ 3, 2025 EST
Innovating with Google Cloud Artificial Intelligence Earned דצמ 3, 2025 EST
Gemini for end-to-end SDLC Earned דצמ 3, 2025 EST
Innovating with Data and Google Cloud - בעברית Earned דצמ 3, 2025 EST
Data Management and Storage in the Cloud Earned דצמ 3, 2025 EST
Prepare Data for ML APIs on Google Cloud Earned דצמ 2, 2025 EST
Build a Secure Google Cloud Network Earned דצמ 2, 2025 EST
Set Up an App Dev Environment on Google Cloud Earned דצמ 2, 2025 EST
Implementing Cloud Load Balancing for Compute Engine Earned דצמ 2, 2025 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned דצמ 2, 2025 EST
Introduction to Data Analytics in Google Cloud Earned דצמ 2, 2025 EST
Digital Transformation with Google Cloud - בעברית Earned דצמ 2, 2025 EST
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned דצמ 1, 2025 EST
Classify Images with TensorFlow on Google Cloud Earned דצמ 1, 2025 EST
Enrich Metadata and Discovery of BigLake Data Earned דצמ 1, 2025 EST
Build a Data Mesh with Dataplex Earned דצמ 1, 2025 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned דצמ 1, 2025 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned נוב 30, 2025 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned נוב 30, 2025 EST
Understanding Google Cloud Security and Operations - בעברית Earned נוב 29, 2025 EST
Gemini for Application Developers Earned נוב 29, 2025 EST
Put It All Together: Prepare for a Cloud Security Analyst Job Earned נוב 28, 2025 EST
Detect, Respond, and Recover from Cloud Cybersecurity Attacks Earned נוב 27, 2025 EST
Cloud Security Risks: Identify and Protect Against Threats Earned נוב 27, 2025 EST
Strategies for Cloud Security Risk Management Earned נוב 27, 2025 EST
Introduction to Security Principles in Cloud Computing Earned נוב 26, 2025 EST
AI Boost Bites: Tame Your Inbox with AI Earned נוב 26, 2025 EST
AI Boost Bites: AI Power-Ups for Google Workspace Earned נוב 26, 2025 EST
AI Boost Bites: Your Personal Feedback Agent Earned נוב 26, 2025 EST
Get Started with Eventarc Earned נוב 19, 2025 EST
Implement CI/CD Pipelines on Google Cloud Earned נוב 19, 2025 EST
Build Infrastructure with Terraform on Google Cloud Earned נוב 19, 2025 EST
Develop Gen AI Apps with Gemini and Streamlit Earned נוב 18, 2025 EST
Mitigate Threats and Vulnerabilities with Security Command Center Earned נוב 18, 2025 EST
Manage Kubernetes in Google Cloud Earned נוב 18, 2025 EST
Create ML Models with BigQuery ML Earned נוב 18, 2025 EST
Gen AI Agents: Transform Your Organization Earned נוב 18, 2025 EST
Boost Productivity with Gemini in BigQuery Earned נוב 17, 2025 EST
Work with Gemini Models in BigQuery Earned נוב 17, 2025 EST
Using BigQuery Machine Learning for Inference Earned נוב 16, 2025 EST
Gemini for Data Scientists and Analysts Earned נוב 16, 2025 EST
Prompt Design in Vertex AI Earned נוב 15, 2025 EST
Responsible AI: Applying AI Principles with Google Cloud Earned נוב 15, 2025 EST
Introduction to Responsible AI - בעברית Earned נוב 15, 2025 EST
Introduction to Large Language Models - בעברית Earned נוב 15, 2025 EST
Introduction to Generative AI - בעברית Earned נוב 15, 2025 EST

This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.

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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.

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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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This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.

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Welcome to the "AI Infrastructure: Networking Techniques" course. In this course, you'll learn to leverage Google Cloud's high-bandwidth, low-latency infrastructure to optimize data transfer and communication between all the components of your AI system. By the end, you'll grasp the critical role networking plays across the entire AI pipeline from data ingestion and training to inference and be able to apply best practices to ensure your workloads run at maximum speed.

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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.

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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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In this course, you’ll take a comprehensive journey through the storage solutions available on Google Cloud, specifically tailored for AI and high-performance computing (HPC) workloads. You’ll learn how to choose the right storage for each stage of the ML lifecycle. You’ll explore how to optimize for I/O performance during training, manage massive datasets for data preparation, and serve model artifacts with low latency. Through practical examples and demonstrations, you’ll gain the expertise to design robust storage solutions that accelerate your AI innovation.

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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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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 applications.

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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.

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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, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.

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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 NotebookLM. 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 s 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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Welcome to the Cloud TPUs course. We'll explore the advantages and disadvantages of TPUs in various scenarios and compare different TPU accelerators to help you choose the right fit. You'll learn strategies to maximize performance and efficiency for your AI models and understand the significance of GPU/TPU interoperability for flexible machine learning workflows. Through engaging content and practical demos, we'll guide you step-by-step in leveraging TPUs effectively.

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Curious about the powerful hardware behind AI? This course breaks down performance-optimized AI computers, showing you why they're so important. We'll explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them. By the end, you'll know exactly how to pick the right compute for your AI projects, helping you make smart choices for your AI workkoads.

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Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.

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Earn a skill badge by completing the Protect Cloud Traffic with Chrome Enterprise Premium Security skill badge course, where you learn how to leverage Chrome Enterprise Premium to provide secure access to critical apps and services, improve your security posture with a modern Zero Trust platform, securely provide access to resources using identity and context-aware access control, and support hybrid cloud workloads using Client Connector.

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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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Earn an introductory skill badge by completing the Get Started with Google Workspace Tools course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.

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AI inference is the process of using a trained machine learning model to make predictions on new, unseen data by applying learned patterns. This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI inference services on Cloud Run. It is useful for those familiar with cloud-based serverless application deployment solutions, but who may not have experience with running AI inference using Google Cloud serverless products. The course includes examples that deploys a model for AI inference with GPUs and integrates gen AI apps with data storage services.

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This course is designed for Google Cloud developers and DevOps engineers who have basic knowledge of the Google Cloud console and are responsible for configuring Gemini Code Assist for an organization. The course introduces the benefits of Gemini Code Assist and compares the features of the different Gemini Code Assist editions. The course also shows you how to configure and manage Gemini Code Assist within an organization.

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This course is designed for app developers and DevOps engineers who want to work smarter by using Gemini CLI, a generative AI agent made for the terminal and powered by Gemini. This course discusses Gemini CLI installation and configuration, and introduces use cases and security best practices. It explains commands, tools, MCP servers, and extensions. With a hands-on exercise, you'll install and configure Gemini CLI and use it to analyze code and build and modify an app.

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Designed for developers of all levels, this course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud. From intelligent code suggestions and auto-completion to real-time error detection and refactoring assistance, you'll discover how Gemini Code Assist can significantly enhance your productivity and code quality, and save valuable time to focus on more productive and enjoyable tasks.

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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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This course introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of 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.

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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 Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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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 to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.

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Enhance the navigation experience of your website by using generative AI to provide a better search experience for your users. In this course, you learn how to use Vertex AI Search to provide your website users a generative search experience enabling them to discover content offered by the website. As a website editor, you also learn how to use generative AI to quickly and efficiently translate and improve the content using suggestions.

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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.

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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 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 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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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud. 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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בארגונים מסורתיים רבים משתמשים במערכות ובאפליקציות מדורות קודמים, וקשה לבצע באמצעותן התאמה לעומס ופעולות מהירות הדרושות כדי לעמוד בציפיות מודרניות של לקוחות. מנהיגים עסקיים וקובעי מדיניות IT צריכים כל הזמן לבחור בין תחזוקה של מערכות מדורות קודמים לבין השקעה במוצרים ובשירותים חדשים. בקורס הזה נבחן את האתגרים הנובעים משימוש בתשתית IT מיושנת, ואיך בעלי עסקים יכולים לבצע מודרניזציה של תשתיות בעזרת טכנולוגיית ענן. הקורס מתחיל בהבנה מעמיקה של אפשרויות המחשוב השונות הזמינות בענן ופירוט היתרונות של כל אחת מהאפשרויות. לאחר מכן נבחן את האפשרויות למודרניזציה של האפליקציות ושל ממשקי API (ממשק תכנות יישומים). בקורס מתוארים גם מגוון פתרונות של Google Cloud שיכולים לשפר את תהליך פיתוח המערכות וניהולן בעסקים שונים, כמו Compute Engine,‏ App Engine ו-Apigee.

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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. 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 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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טכנולוגיית הענן לבדה מספקת לעסק חלק קטן בלבד מהערך האמיתי שלה. כשהיא משולבת עם נתונים בנפח רב מאוד, נוצרת העוצמה שמאפשרת להפיק ערך וליצור חוויות חדשות ללקוחות. במסגרת הקורס הזה תלמדו מהם נתונים, איך השתמשו בהם בעבר בחברות לצורך קבלת החלטות ולמה הם קריטיים כל כך ללמידה חישובית. בנוסף, בקורס הזה יוצגו ללומדים מושגים טכניים כמו נתונים מובְנים ולא מובְנים, מסד נתונים, מחסן נתונים (data warehouse) ואגמי נתונים (data lakes). בהמשך, הקורס יעסוק במוצרי Google Cloud הנפוצים ביותר בתחום הנתונים, ובמוצרים כאלה ששיעור השימוש בהם גדל במהירות הרבה ביותר.

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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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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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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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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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מהי טכנולוגיית ענן ומהו מדע הנתונים? וחשוב יותר, איך הם יכולים לעזור לכם, לצוות שלכם ולעסק שלכם? קורס המבוא הזה בנושא טרנספורמציה דיגיטלית מתאים למי שרוצה ללמוד על טכנולוגיית הענן כדי להתמקצע ולהצטיין בעבודתו וכדי לעזור בפיתוח העתיד של העסק. בקורס יוגדרו מונחי יסוד כגון הענן, נתונים וטרנספורמציה דיגיטלית. בנוסף, נבחן דוגמאות של חברות מרחבי העולם שמשתמשות בטכנולוגיית הענן כדי לבצע טרנספורמציה בעסק. הקורס כולל סקירה של סוגי ההזדמנויות שיש לחברות ושל האתגרים הנפוצים שחברות מתמודדות איתם במהלך טרנספורמציה דיגיטלית. הקורס גם מדגים איך עמודי התווך של פתרונות Google Cloud יכולים לעזור בתהליך. חשוב לומר: טרנספורמציה דיגיטלית לא קשורה רק לשימוש בטכנולוגיות חדשות. כדי הטרנספורמציה תהיה מלאה, ארגונים צריכים גם ליישם חדשנות ולפתח דפוס חשיבה שמקדם חדשנות בכל התחומים והצוותים. השיטות המומלצות המתוארות בקורס יעזרו לכם להשיג את המטרה הזו.

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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.

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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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Complete the Enrich Metadata and Discovery of BigLake Data skill badge course to demonstrate skills in BigQuery, BigLake, and Dataplex Universal Catalog. You create BigLake tables and enrich metadata management and discovery of the table data.

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Complete the introductory Build a Data Mesh with Dataplex skill badge to demonstrate skills in the following: building a data mesh with Dataplex to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in tagging assets, assigning IAM roles, and assessing data quality in Dataplex.

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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

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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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הקורס בוחן ניהול עלויות, אבטחה ותפעול בענן. ראשית, מוסבר איך עסקים יכולים לרכוש שירותי IT מספק שירותי ענן ולשמר חלק מהתשתית שלהם או לבחור לא לשמר אותה בכלל. שנית, הקורס מתאר איך האחריות על אבטחת נתונים מתחלקת בין ספק שירותי הענן לעסק, וסוקר את אבטחת ההגנה לעומק (defense-in-depth) שמובנית ב-Google Cloud. לבסוף, הקורס מתייחס לכך שצוותי IT ומנהלי העסק צריכים לשנות את החשיבה על ניהול משאבי IT בענן, ונוגע באופן שבו כלי ניטור המשאבים ב-Google Cloud יכולים לסייע להם לשמור על שליטה וניראות בסביבת הענן שלהם.

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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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This is the fifth of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll combine and apply key concepts such as cloud security principles, risk management, identifying vulnerabilities, incident management, and crisis communications in an interactive capstone project. Additionally, you'll finalize your resume updates and put to practice all the new interview techniques you've learned, preparing you to confidently apply for and interview for jobs in the field.

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This is the fourth of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll focus on developing capabilities in logging, security, and alert monitoring, along with techniques for mitigating attacks. You'll gain valuable knowledge in customizing threat feeds, managing incidents, handling crisis communications, conducting root cause analysis, and mastering incident response and post-event communications. Using Google Cloud tools, you'll learn to identify indicators of compromise and prepare for business continuity and disaster recovery. Alongside these technical skills, you'll continue updating your resume and practicing interview techniques.

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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 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 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 video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.

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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.

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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.

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Earn a skill badge by completing the Get Started with Eventarc skill badge course, where you use Eventarc to create event triggers for different resources including Pub/Sub topics and Cloud Storage buckets.

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Earn the intermediate skill badge by completing the Implement CI/CD Pipelines on Google Cloud skill badge course where you learn how to use Artifact Registry, Cloud Build, and Cloud Deploy. You interact with the Google Cloud console, Google Cloud CLI, Cloud Run, and GKE. This course teaches you how to build continuous integration pipelines, store and secure artifacts, scan for vulnerabilities, attest to the validity of approved releases. Additionally, you get hands-on experience deploying applications to both GKE and Cloud Run.

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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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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.

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Complete the intermediate Mitigate Threats and Vulnerabilities with Security Command Center skill badge course to demonstrate skills in the following: preventing and managing environment threats, identifying and mitigating application vulnerabilities, and responding to security anomalies.

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.

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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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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.

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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.

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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.

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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.

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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. Duet AI was renamed to Gemini, our next-generation model.

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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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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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