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Choukri El Ouastani

Member since 2022

Bronze League

46390 points
Build with Gemini Earned Eyl 29, 2026 EDT
Agentic Strategy: Discover, Design, and Prototype Earned Eyl 13, 2026 EDT
Liftoff with Google Antigravity: Build a Video Game with AI Earned Eyl 6, 2026 EDT
Govern Agent Access with Gemini platform Earned Ağu 4, 2026 EDT
Add Agents to Gemini Earned Ağu 4, 2026 EDT
Deploy Gemini with Workspace Data Sources and Model Armor Earned Ağu 3, 2026 EDT
Serverless Data Processing with Dataflow: Develop Pipelines Earned Tem 17, 2026 EDT
Find, Explore and Deploy Model Garden Models Earned Tem 2, 2026 EDT
Evaluate and Improve Agent Development Kit Agents Earned Haz 25, 2026 EDT
Accelerate Development with Antigravity Earned Haz 23, 2026 EDT
Deploy an Agent with Agent Development Kit (ADK) Earned Haz 20, 2026 EDT
Orchestrate Data Lifecycle Automation with Data Agents Earned Haz 19, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned Haz 18, 2026 EDT
Model Armor: Securing AI Deployments Earned Haz 5, 2026 EDT
[DEPRECATED] Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service Earned May 20, 2026 EDT
Deploy Multi-Agent Systems with Gemini Enterprise Agent Platform Earned May 19, 2026 EDT
Manage Agent Memory and State Earned May 18, 2026 EDT
Add Agent Capabilities With Tools Earned May 17, 2026 EDT
Understand Google Cloud Agents Earned May 16, 2026 EDT
Deploy Multi-Agent Architectures Earned Nis 4, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK) Earned Mar 25, 2026 EDT
Büyük Dil Modellerine Giriş Earned Mar 22, 2026 EDT
Build a Multimodal GenAI Pipeline with BigQuery Earned Mar 21, 2026 EDT
Data Warehousing for Partners: Migrate Data to BigQuery Earned Mar 19, 2026 EDT
Google Skills Arcade Base Camp January 2026 Earned Oca 28, 2026 EST
Deliver Effective Product Demos Earned Ara 24, 2025 EST
Build Data Analytics Solutions on Google Cloud Earned Ara 23, 2025 EST
Discover Business Value for Customers Earned Ara 12, 2025 EST
Generative AI Explorer : Vertex AI Earned Ara 2, 2025 EST
Evaluate Gen AI model and agent performance Earned Ağu 15, 2025 EDT
Deploy and Evaluate Model Garden Models Earned Ağu 14, 2025 EDT
Deploy a RAG application with vector search in Firestore Earned Ağu 11, 2025 EDT
Implement Hybrid Search Earned Ağu 9, 2025 EDT
Implement RAG with Gemini platform Earned Ağu 8, 2025 EDT
Create Embeddings, Vector Search, and RAG with BigQuery Earned Ağu 8, 2025 EDT
Work with Gemini Models in BigQuery Earned Ağu 7, 2025 EDT
Edit images with Imagen Earned Ağu 7, 2025 EDT
Generate and Edit Media in Agent Platform Earned Ağu 5, 2025 EDT
Empower Gen AI Apps with Tool Use Earned Tem 19, 2025 EDT
Extend Gemini with controlled generation and Tool use Earned Tem 19, 2025 EDT
[DEPRECATED] Integrate Vertex AI Search and Conversation into Voice and Chat Apps Earned Haz 4, 2025 EDT
Data Lake Modernization on Google Cloud: Cloud Composer Earned May 9, 2025 EDT
Görüntülere Altyazı Ekleme Modelleri Oluşturma Earned Nis 17, 2025 EDT
Görüntü Üretmeye Giriş Earned Nis 17, 2025 EDT
Dönüştürücü Modelleri ve BERT Modeli Earned Nis 17, 2025 EDT
Kodlayıcı-Kod Çözücü Mimarisi Earned Mar 8, 2025 EST
Dikkat Mekanizması Earned Mar 8, 2025 EST
Boost Productivity with Gemini in BigQuery Earned Oca 13, 2025 EST
Text Prompt Engineering Techniques Earned Oca 5, 2025 EST
[DEPRECATED] Generative AI Fundamentals Earned Oca 5, 2025 EST
Monitor and Manage Data in BigQuery Earned Ara 31, 2024 EST
Vertex AI Studio'ya Giriş Earned Ara 30, 2024 EST
Migrate Cloudera to Google Cloud Earned Ara 29, 2024 EST
Sorumlu Yapay Zeka: Google Cloud ile Yapay Zeka İlkelerini Uygulama Earned Ara 29, 2024 EST
[DEPRECATED] Sorumlu Yapay Zekaya Giriş Earned Ara 29, 2024 EST
[DEPRECATED] Generative AI for Business Leaders Earned Ara 29, 2024 EST
Build a Data Mesh with Knowledge Catalog Earned Eki 22, 2024 EDT
BigQuery Verilerinden Analiz Elde Etme Earned Eki 20, 2024 EDT
Data Warehousing for Partners: Design in BigQuery Earned Eyl 27, 2024 EDT
Data Warehousing for Partners: Enable Google Cloud Customers Earned Eyl 24, 2024 EDT
Automate Data Migrations to BigQuery Earned Nis 14, 2024 EDT
Implement DevOps Workflows in Google Cloud Earned Mar 31, 2024 EDT
Build a Data Warehouse with BigQuery Earned Mar 27, 2024 EDT
Developing a Google SRE Culture Earned Mar 18, 2024 EDT
Build Infrastructure with Terraform on Google Cloud Earned Oca 3, 2024 EST
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma Earned Kas 19, 2023 EST
Develop Serverless Applications on Cloud Run Earned Tem 15, 2023 EDT
Deploy Kubernetes Applications on Google Cloud Earned Haz 6, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned May 27, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned May 8, 2022 EDT

This is intended for individuals who completed the Build with Gemini workshop to validate the knowledge gained in that workship and earn a Skill Badge

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Step into the future with Agentic Strategy: Discover, Design, and Prototype. This course allows you to master the Google Agentic AI Transformation Framework and move beyond chatbots to autonomous teammates. Through a retail use case, you will learn to quantify business value, prioritize AI projects, map critical user journeys, and build functional prototypes using no-code tools like Google AI Studio and Gemini Enterprise. This course provides a solid roadmap necessary for business and technical leaders to lead their organization into the agentic AI era. Explore other content in the Gemini Agent Ready (GEAR) program.

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In this course, you'll learn to build software at a propulsive speed by orchestrating agents in Google Antigravity. This hands-on course will first guide you to install and get started with Antigravity by making a Hello, World(s)! app. Next, you'll use Firebase to deploy that app. Finally, you'll build a video game, Voyager, by orchestrating agents in Antigravity to work in parallel. Explore other content in the Gemini Agent Ready (GEAR) program.

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In this challenge lab, you will act as a cloud engineer supporting the Cymbal Pools finance team. Your mission is to deploy a BigQuery-enabled agent to Agent Runtime to help process invoice data using natural language. Rather than building from scratch, you inherit an unsecured deployment. You must establish basic data governance by configuring the Agent Development Kit (ADK), deploying the agent with a dedicated SPIFFE identity, identifying permission blocks, and applying least-privilege IAM roles so the agent can safely query and update the BigQuery database from the Agent Runtime Playground.

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In this challenge lab, you will demonstrate your ability to add agents to Gemini. You will build an agent with Agent Designer, and you will build a no-code agent with Agent Development Kit, deploy it to Agent Engine, and add it to Gemini.

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In this challenge lab, you act as a Security Engineer deploying a secure Gemini environment for Cymbal Bank. You will ground Gemini in web search and internal Workspace sources to ensure accurate, contextual responses. To maintain compliance, you will configure Model Armor policies to filter sensitive data and block threats like prompt injections and malicious URLs. Finally, you will manage specific end-user features to customize the AI experience safely

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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

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Model Garden on Gemini platform is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.

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Complete the Evaluate and Improve Agent Development Kit Agents skill badge to demonstrate your ability to use ADK's evaluation tools to "hill climb" — making measurable, iterative improvements to an agent. You will run an initial evaluation to establish a baseline, apply optimization techniques, and re-evaluate the agent to measure your success.

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Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.

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Complete the Orchestrate Data Lifecycle Automation with Data Agents skill badge to demonstrate your proficiency in modernizing data infrastructure using AI-driven automation. Emphasis is placed on acting as an 'Agent Orchestrator'—leveraging specialized Data Agents to build resilient Dataform pipelines, enforce Dataplex governance, and accelerate data science workflows in Colab Enterprise. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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

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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.

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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Agent Runtime on Gemini Enterprise Agent Platform to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Runtime. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions

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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions

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This course provides an overview of building AI Agents on Google Cloud. You discover how to boost employee productivity with Gemini and craft dynamic customer experiences using Conversational Agents and Customer Experience (CX) Studio. You learn how to leverage Gemini alongside the Agent Development Kit (ADK) to design custom, multi-agent architectures. You also explore choosing the right tool for each use case, grounding models in enterprise data, and deploying agents securely into production.

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Complete the advanced Deploy Multi-Agent Architectures skill badge to demonstrate skills in the following: building multi-agent systems with ADK, connecting agents with the Agent-to-Agent (A2A) protocol, integrating external tools using the Model Context Protocol (MCP), and deploying a complete multi-agent solution to Agent Engine. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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

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Giriş seviyesindeki bu mikro öğrenme kursunda; büyük dil modellerinin (LLM) ne olduğu, hangi kullanım alanlarında kullanılabilecekleri ve istem ayarlama ile LLM performansını nasıl artırabileceğiniz ele alınmaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da yer almaktadır.

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Complete the Build a "Data to AI" Pipeline with BigQuery and Gemini skill badge to demonstrate your proficiency in modernizing legacy product catalogs through end-to-end data engineering and AI orchestration. Emphasis is placed on unifying structured and unstructured data using BigLake, leveraging Gemini for multimodal processing, and deploying scalable machine learning solutions via Vertex AI. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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This course identifies best practices for migrating data warehouses to BigQuery and the key skills required to perform successful migration.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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This course is designed to enhance your demonstration skills and help you deliver impactful presentations.

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This Data Analytics course consists of a series of advanced-level labs designed to validate your proficiency in using Google Cloud services. Each lab presents a set of the required tasks that you must complete with minimal assistance.

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The course aims to train Google technical sales partners on the business value discovery process using proprietary content.

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This content is deprecated. Please see the latest version of the course, here.

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Complete the Evaluate Gen AI model and agent performance skill badge to demonstrate your ability to use the Gen AI evaluation service. You will evaluate models to select the best model for a given task, compare models against each other and evaluate the performance of agents. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.

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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.

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Learn how to create Hybrid Search applications using Vector Search on Gemini platform to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.

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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Gemini platform APIs, vector stores, and the LangChain framework.

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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

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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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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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This course dives into the world of media creation with Gemini Enterprise Agent Platform using Nano Banana and Veo. Learn to design text and image-based prompts to produce high-quality, consistent images, and captivating, cinematic video clips. You'll also learn to refine generated assets using core editing functions. Finally, this course guides you through multi-tool workflow implementations for creative control and consistency, empowering you to transform images into video clips and leverage Gemini for prompt writing assistance and feedback.

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An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.

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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"

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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.

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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.

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Bu kurs, derin öğrenmeyi kullanarak görüntülere altyazı ekleme modeli oluşturmayı öğretmektedir. Kurs sırasında görüntülere altyazı ekleme modelinin farklı bileşenlerini (ör. kodlayıcı ve kod çözücü) ve modelinizi eğitip değerlendirmeyi öğreneceksiniz. Bu kursu tamamlayan öğrenciler, kendi görüntülere altyazı ekleme modellerini oluşturabilecek ve bu modelleri görüntülere altyazı oluşturmak için kullanabilecek.

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Bu kursta, görüntü üretme alanında gelecek vadeden bir makine öğrenimi modelleri ailesi olan "difüzyon modelleri" tanıtılmaktadır. Difüzyon modelleri fizikten, özellikle de termodinamikten ilham alır. Geçtiğimiz birkaç yıl içinde, gerek araştırma gerekse endüstri alanında difüzyon modelleri popülerlik kazandı. Google Cloud'daki son teknoloji görüntü üretme model ve araçlarının çoğu, difüzyon modelleri ile desteklenmektedir. Bu kursta, difüzyon modellerinin ardındaki teori tanıtılmakta ve bu modellerin Vertex AI'da nasıl eğitilip dağıtılacağı açıklanmaktadır.

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Bu kurs, dönüştürücü mimarisini ve dönüştürücülerden çift yönlü kodlayıcı temsilleri (BERT - Encoder Representations from Transformers) modelini tanıtmaktadır. Kursta, öz dikkat mekanizması gibi dönüştürücü mimarisinin ana bileşenlerini ve BERT modelini oluşturmak için dönüştürücünün nasıl kullanıldığını öğreneceksiniz. Ayrıca sınıflandırma, soru yanıtlama ve doğal dil çıkarımı gibi BERT'in kullanılabileceği çeşitli görevler hakkında da bilgi sahibi olacaksınız. Kursun tahmini süresi 45 dakikadır.

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Bu kursta, kodlayıcı-kod çözücü mimarisi özet olarak anlatılmaktadır. Bu mimari; makine çevirisi, metin özetleme ve soru yanıtlama gibi "sıradan sıraya" görevlerde yaygın olarak kullanılan, güçlü bir makine öğrenimi mimarisidir. Kursta, kodlayıcı-kod çözücü mimarisinin ana bileşenlerini ve bu modellerin nasıl eğitilip sunulacağını öğreneceksiniz. Laboratuvarın adım adım açıklamalı kılavuz bölümünde ise sıfırdan şiir üretmek için TensorFlow'da kodlayıcı-kod çözücü mimarisinin basit bir uygulamasını yazacaksınız.

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Bu kursta nöral ağların, giriş sırasının belirli bölümlerine odaklanmasına olanak tanıyan güçlü bir teknik olan dikkat mekanizması tanıtılmaktadır. Kursta, dikkat mekanizmasının çalışma şeklini ve makine öğrenimi, metin özetleme ve soru yanıtlama gibi çeşitli makine öğrenimi görevlerinin performansını artırmak için nasıl kullanılabileceğini öğreneceksiniz.

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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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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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This skill badge aims to evaluate a partner's ability to utilize BigQuery's features and capabilities to manage and analyze large datasets. Learners will gain hands-on experience through labs and achieve solid understanding of BigQuery's foundational concepts and features.

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Bu kursta Vertex AI Studio tanıtılmaktadır. Bu araç, üretken yapay zeka modelleriyle etkileşime geçmek, kurumsal fikirlerin prototipini oluşturmak ve bunları gerçek hayatta uygulamak için kullanılır. Gerçek hayattan kullanım alanları, etkileşimli dersler ve uygulamalı laboratuvarlar aracılığıyla, ilk istemden son ürüne uzanan yaşam döngüsünü keşfedecek ve çoklu format destekli Gemini uygulamaları, istem tasarımı, istem mühendisliği ve model ayarlama konularında Vertex AI Studio'dan nasıl yararlanabileceğinizi öğreneceksiniz. Bu kursun amacı, Vertex AI Studio'yu kullanarak projelerinizde üretken yapay zekadan yararlanabilmenizi sağlamaktır.

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This skill badge aims to evaluate a partner's ability to migrate data from Cloudera to Google Cloud Platform. Learners will gain hands-on experience through labs and achieve comprehensive knowledge and practical skills for migrating data from Cloudera to Google Cloud Platform.

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Kurumsal yapay zeka ve makine öğreniminin kullanımı arttıkça, bu teknolojileri sorumlu bir şekilde geliştirmenin önemi de artıyor. Birçok kişi için sorumlu yapay zeka hakkında konuşmak, bunu uygulamaya geçirmekten daha kolaydır. Kuruluşunuzda sorumlu yapay zekayı nasıl hayata geçireceğinizi öğrenmek istiyorsanız bu kurs tam size göre. Bu kursta, kendi sorumlu yapay zeka yaklaşımınızı geliştirirken size rehberlik edecek bir çerçeve oluşturmak adına Google Cloud'un bu süreci günümüzde nasıl yürüttüğünü, en iyi uygulama örneklerini ve edindiğimiz tecrübeleri keşfedeceksiniz.

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Giriş seviyesindeki bu mikro öğrenme kursu, sorumlu yapay zekanın ne olduğunu, neden önemli olduğunu ve Google'ın sorumlu yapay zekayı ürünlerinde nasıl uyguladığını açıklamayı amaçlamaktadır. Ayrıca Google'ın 3 yapay zeka ilkesini de tanıtır.

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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.

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Complete the introductory Build a Data Mesh with Knowledge Catalog skill badge to demonstrate skills in the following: building a data mesh with Knowledge Catalog 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 Knowledge Catalog.

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Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.

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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.

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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.

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This skill badge aims to provide partners an introduction to BigQuery Data Transfer Service and Migration Service, two powerful tools for managing and migrating data in the cloud. Learners will learn how to leverage these tools to efficiently migrate and manage data, and gain hands-on experience through labs.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating and managing Git repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.

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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.

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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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Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta Cloud Storage, Identity and Access Management, Cloud Functions ve Pub/Sub gibi teknolojilerin temel özelliklerini kullanarak depolama odaklı bulut altyapısı oluşturma ve bu altyapıyla bağlantı kurmayı öğreneceksiniz.

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Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.

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

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

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