12 053 cours
欢迎学习 Cloud TPU 课程。我们将探讨 TPU 在不同场景下的优势和劣势，并比较不同的 TPU 加速器，以帮助您选择合适的加速器。您将了解可通过哪些策略充分提高 AI 模型的性能和效率，并理解 GPU/TPU 互操作性对于创建灵活的机器学习工作流程的重要性。通过引人入胜的课程内容和实际演示，您将逐步了解如何有效利用 TPU。
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In this course you will gain insights into content marketing management, focusing on product creation, management, and branding strategies. Delve into pricing strategies like customer value, cost-based, and competition-based pricing, and learn the best approaches for product launches. Understand the product lifecycle, deliver value through pricing, and master distribution channels for optimal market reach.
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This is a self-paced lab that takes place in the Google Cloud console. In this lab, you create two managed instance groups in the same region. Then, you configure an Internal Load Balancer with the instances groups as the backends.
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Code and run your first Java program in minutes without installing anything! This course is designed for learners with limited coding experience, building on a solid foundation of Java, learners will dive into key Java classes, interfaces, and frameworks. The modules in this course cover developer best practices, data handling, and connecting to web-based systems. Completion of an introductory Java sequence such as Codio's Hands-On Java Introduction is recommended. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.
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De nombreuses entreprises traditionnelles utilisent d'anciens systèmes et d'anciennes applications qui ne peuvent plus satisfaire les attentes des clients d'aujourd'hui. Les chefs d'entreprise doivent régulièrement choisir entre deux options : entretenir leurs systèmes informatiques vieillissants ou investir dans de nouveaux produits et services. Le cours ""Modernize Infrastructure and Applications with Google Cloud"" aborde ces problématiques et propose des solutions pour les résoudre à l'aide de la technologie cloud. Ce cours fait partie du parcours de formation Cloud Digital Leader. Il vise à aider les participants à évoluer dans leur poste et à bâtir l'avenir de leur entreprise.
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Modern Security Operations, based on Google's Autonomic Security Operations framework and Continuous Detection, Continuous Response (CD/CR) methodology is a combination of philosophies, practices, and tools that improve an organization's ability to withstand security attacks through an adaptive, agile, and highly automated approach to threat management. In this introductory course, learners will gain a holistic perspective on leading their organizations through modernizing their security operations program.
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En este curso basado en un proyecto, aprenderás a crear un programa en Python para resolver ecuaciones lineales, y explorarás objetos, sentencias y funciones de Python para procesar textos y números. Al finalizar este proyecto habrás creado una aplicación que ayudará a los estudiantes y profesores a practicar con expresiones y ecuaciones lineales o de primer grado. Durante el proceso aprenderás a usar Jupyter para editar y ejecutar programas de Python; utilizar objetos con datos textuales y numéricos y en listas; controlar la secuencia de ejecución del programa; definir tus propias funciones y utilizar funciones de Python. En varios casos partiremos de algoritmos para crear programas y funciones. Esta experiencia servirá para comenzar a desarrollar programas para otras aplicaciones en matemática, ciencia, ingeniería y tecnología.
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In this intermediate-level course, you’ll learn how to model and secure financial data in Power BI using real-world business scenarios. You’ll start by importing General Ledger, Cost Center, and Budget data, then design a star-schema model that supports accurate, high-performing analytics. Through guided demos and hands-on practice, you’ll define relationships, create DAX measures for Gross Margin, and validate your model structure for reliable reporting. Next, you’ll apply Row-Level Security (RLS) and Role-Based Access Control (RBAC) to ensure sensitive data stays protected as you publish to Power BI Service. Along the way, you’ll explore how modeling and security intersect—where table structure influences filter logic and access rules affect collaboration. By the end of the course, you’ll have the confidence to build, test, and deploy Power BI dashboards that are both powerful and secure, ready for real enterprise environments.
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Explore Infrastructure as Code concepts without installing anything! This course is designed for beginning learners, providing a solid foundation of managing cloud resources using Infrastructure as Code techniques. Some of these techniques include: Ansible, Docker, Kubernetis, and Terraform. The modules in this course cover the configuration of containers, deploying those containers, and finally configuring the cloud. At the end of the course, learners will be able to directly implement these techniques to help them manage their own cloud resources. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and suggested exploration examples, building a deeper understanding by doing. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling answer blocks) to small, approachable exercises that take minutes instead of hours.
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Este curso ajuda você a se preparar para o exame Professional Cloud Engineer. Você vai aprender sobre os domínios do Google Cloud abordados no exame e como criar um plano de estudos para melhorar seu conhecimento sobre o assunto.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow. Prerequisites: The Serverless Data Processing with Dataflow course series builds on the concepts covered in the Data Engineering specialization. We recommend the following prerequisite courses: (i)Building batch data pipelines on Google Cloud : covers core Dataflow principles (ii)Building Resilient Streaming Analytics Systems on Google Cloud : covers streaming basics concepts like windowing, triggers, and watermarks >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<
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This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles. In practical, hands on assignments, you will learn how to simulate t-tests to learn which p-values you can expect, calculate likelihood ratio's and get an introduction the binomial Bayesian statistics, and learn about the positive predictive value which expresses the probability published research findings are true. We will experience the problems with optional stopping and learn how to prevent these problems by using sequential analyses. You will calculate effect sizes, see how confidence intervals work through simulations, and practice doing a-priori power analyses. Finally, you will learn how to examine whether the null hypothesis is true using equivalence testing and Bayesian statistics, and how to pre-register a study, and share your data on the Open Science Framework. All videos now have Chinese subtitles. More than 30.000 learners have enrolled so far! If you enjoyed this course, I can recommend following it up with me new course "Improving Your Statistical Questions"
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