Coursera Google Cloud on CourseEye - The Eye to Your Ideal Online Course

Trecho extraído do curso: "A melhor maneira de se preparar para o exame é ter competência nas habilidades que o trabalho exige." Este curso usa uma abordagem de cima para baixo com o objetivo de revelar as habilidades e o conhecimento que você já tem e apontar as áreas que precisam melhorar. Use este curso para criar seu próprio plano de estudo personalizado. Ele ajudará você a se preparar melhor e a desenvolver e praticar as habilidades necessárias para realizar este trabalho. O curso segue a

Preparing for the Google Cloud Professional Cloud Architect Exam 日本語版 (Coursera)

https://www.coursera.org/learn/preparing-cloud-professional-cloud-architect-exam-jp

コースより抜粋: 「最善の試験対策は職務に必要なスキルを身に付けることである」このコースではトップダウンアプローチを用いて既知の知識とスキルを把握し、情報とスキルが不十分な分野を特定します。本コースを受講することにより、独自の対策計画を立てることができます。わかっていることとわからないことを明確にし、この職務の担当者に必要なスキルの習得と向上にお役立てください。本コースでは試験ガイドの概要に沿って、受講者が特定の分野と関連する概念を十分に理解しているか、またはさらなる学習が必要かを判断できるように、「判断基準」となる概念を提示します。また、ケース分析、技術的に注意すべきポイントの特定、提案ソリューションの開発などの認知スキルを含む主要な職務スキルについて学び、実践する機会も用意されています。これらは職務スキルであると同時に試験スキルでもあります。また、アクティビティトラッキングチャレンジラボを使って基礎能力もテストします。試験問題と同じような例題と解答も多数用意されており、コースの最後には採点式ではない模擬試験問題と、受験を想定した採点式の模擬試験問題が含まれて

Preparing for the Google Cloud Professional Data Engineer Exam 日本語版 (Coursera)

https://www.coursera.org/learn/preparing-cloud-professional-data-engineer-exam-jp

このコースは、受験資格のある受験者が自信を持って試験を受けられるように支援する情報、およびまだ受験資格のない方が試験対策を進める際に役立つ情報を提供します。

Preparing for Your Associate Cloud Engineer Journey (Coursera)

https://www.coursera.org/learn/preparing-cloud-associate-cloud-engineer-exam

This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

Preparing for Your Associate Cloud Engineer Journey en Español (Coursera)

https://www.coursera.org/learn/preparing-cloud-associate-cloud-engineer-exam-es

Este curso te permite estructurar tu preparación para el examen de Associate Cloud Engineer. Aprenderás sobre los dominios de Google Cloud que se incluyen en el examen y la forma de crear un plan de estudio para saber más de ellos.

Preparing for your Professional Cloud Architect Journey (Coursera)

https://www.coursera.org/learn/preparing-cloud-professional-cloud-architect-exam

This course helps learners create a study plan for the PCA (Professional Cloud Architect) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

Preparing for Your Professional Cloud Security Engineer Journey (Coursera)

https://www.coursera.org/learn/preparing-for-your-professional-cloud-security-engineer-journey

This course helps learners prepare for the Professional Cloud Security Engineer (PCSE) Certification exam. Learners will be exposed to and engage with exam topics through a series of lectures, diagnostic questions, and knowledge checks. After completing this course, learners will have a personalized workbook that will guide them through the rest of their certification readiness journey.

Preparing for your Professional Data Engineer Journey (Coursera)

https://www.coursera.org/learn/preparing-cloud-professional-data-engineer-exam

This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

Preparing Google Associate Cloud Engineer Exam em Português (Coursera)

https://www.coursera.org/learn/preparing-cloud-associate-cloud-engineer-exam-pt

Este curso ajuda você a se preparar para o exame Associate 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.

Production Machine Learning Systems (Coursera)

https://www.coursera.org/learn/gcp-production-ml-systems

In this course, we dive into the components and best practices of building high-performing ML systems in production environments. We cover some of the most common considerations behind building these systems, e.g. static training, dynamic training, static inference, dynamic inference, distributed TensorFlow, and TPUs. This course is devoted to exploring the characteristics that make for a good ML system beyond its ability to make good predictions.

Put It All Together: Prepare for a Cloud Data Analyst Job (Coursera)

https://www.coursera.org/learn/put-it-all-together-prepare-for-a-cloud-data-analyst-job

You made it! This is the fifth and final course of the Google Cloud Data Analytics Certificate. There’s no time like the present to start preparing for your job as a Cloud Data Analyst. Let's polish up that resume and refine those interview skills to allow you to show up with confidence for your interview!

Put It All Together: Prepare for a Cloud Security Analyst Job (Coursera)

https://www.coursera.org/learn/put-it-all-together-prepare-for-a-cloud-security-analyst-job

You made it! It’s the fifth and final course of the Google Cloud Cybersecurity Certificate. It’s time to start polishing the resume and getting ready for interviews! In this course, you’ll review cloud security-focused career resources designed to get you job ready!

Recommendation Systems on Google Cloud (Coursera)

https://www.coursera.org/learn/recommendation-models-gcp

In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

Reliable Cloud Infrastructure: Design and Process dalam bahasa Indonesia (Coursera)

https://www.coursera.org/learn/cloud-infrastructure-design-process-id

Kursus ini membekali peserta dengan keterampilan untuk membuat solusi yang sangat andal dan efisien di Google Cloud menggunakan pola desain yang telah terbukti. Kursus ini merupakan kelanjutan dari kursus Architecting with Google Compute Engine atau Architecting with Google Kubernetes Engine dan memberikan pengalaman interaktif dengan teknologi yang dibahas dalam kursus tersebut. Melalui kombinasi presentasi, aktivitas desain, dan lab interaktif, peserta akan mempelajari cara menentukan dan meny

Reliable Cloud Infrastructure: Design and Process em Português Brasileiro (Coursera)

https://www.coursera.org/learn/cloud-infrastructure-design-process-br

Este curso prepara estudantes para criar soluções altamente confiáveis e eficientes no Google Cloud usando padrões de projeto comprovados. Ele é uma continuação do curso "Architecting with Google Compute Engine" ou "Architecting with Google Kubernetes Engine" e exige experiência prática com as tecnologias abordadas nesses dois cursos. Com uma combinação de apresentações, atividades de criação e laboratórios práticos, os participantes aprendem a definir e equilibrar requisitos técnicos e comercia

Reliable Cloud Infrastructure: Design and Process en Español (Coursera)

https://www.coursera.org/learn/cloud-infrastructure-design-process-es

En este curso, los alumnos aprenderán a crear soluciones altamente confiables y eficientes en Google Cloud mediante patrones de diseño comprobados. Es la continuación de los cursos Architecting with Google Compute Engine o Architecting with Google Kubernetes Engine. Se presupone que los equipos tienen experiencia práctica con las tecnologías que se abordan en cualquiera de esos cursos. Mediante una serie de presentaciones, actividades de diseño y labs prácticos, los participantes aprenderán a de

Reliable Cloud Infrastructure: Design and Process 日本語版 (Coursera)

https://www.coursera.org/learn/cloud-infrastructure-design-process-jp

本コースでは、実績ある設計パターンを利用し、信頼性と効率に優れたソリューションを Google Cloud で構築する方法を学習します。本コースは Architecting with Google Compute Engine または Architecting with Google Kubernetes Engine の後続コースであり、これらいずれかのコースで取り上げられているテクノロジーを習得済みであることが受講の前提になります。講義、設計アクティビティ、ハンズオンラボを通して、信頼性と可用性が高く、安全でコスト効率に優れた Google Cloud デプロイメントを設計するためのビジネス要件と技術的要件をバランス良く定義する方法を学びます。このコースでは、以下のスキルについて学習します。 ● 問い、テクニック、設計上の考慮事項からなるツールセットを適用する ● アプリケーションの要件を定義し、KPI、SLO、SLI として具体的に表す ● アプリケーション要件を細分化し、適切なマイクロサービス境界を見つける ●Google Cloud のデベロッパーツールを利用して、

Reliable Google Cloud Infrastructure: Design and Process (Coursera)

https://www.coursera.org/learn/cloud-infrastructure-design-process

This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design

Responsible AI for Developers (CourseraSpecs)

https://www.coursera.org/specializations/responsible-ai-for-developers

Offered by Google Cloud. Build Responsible AI Systems with Google. Learn how to design and build fair, transparent, secure, and safe AI systems

Responsible AI for Developers: Fairness & Bias (Coursera)

https://www.coursera.org/learn/responsible-ai-for-developers-fairness--bias

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.

Responsible AI for Developers: Interpretability & Transparency (Coursera)

https://www.coursera.org/learn/responsible-ai-for-developers-interpretabilitytransparency

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.

Responsible AI: Applying AI Principles with Google Cloud (Coursera)

https://www.coursera.org/learn/responsible-ai-applying-ai-principles-with-google-cloud

This course, Responsible AI: Applying AI Principles with Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Responsible AI: Applying AI Principles with Google Cloud. 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 inte

Scaling with Google Cloud Operations (Coursera)

https://www.coursera.org/learn/understanding-google-cloud-security-and-operations

"Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build th

Securing and Integrating Components of your Application (Coursera)

https://www.coursera.org/learn/securing-integrating-components-app

In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to develop more secure applications, implement federated identity management, and integrate application components by using messaging, event-driven processing, and API gateways. Completing one version of each lab is required. Each lab is available in

Securing and Integrating Components of your Application 日本語版 (Coursera)

https://www.coursera.org/learn/securing-integrating-components-app-jp

このコースでは、アプリケーションデベロッパー向けに、Google Cloud のマネージドサービスをシームレスに統合するクラウドネイティブアプリケーションを設計、開発する方法を説明します。講義、デモ、ハンズオンラボを通して、メッセージング、イベント駆動型処理、API ゲートウェイを使ったセキュリティ性の高いアプリケーションの設計、フェデレーション ID 管理の実装、アプリケーションコンポーネントの統合方法を学習します。各ラボのいずれかのバージョンを完了する必要があります。各ラボは Node.js で利用できるほか、ほとんどの場合、Python または Java でも提供されます。お好みの言語でラボを完了できます。本コースは、「Developing Applications with Google Cloud」シリーズの 2 つ目のコースですこのコースを修了したら、「App Deployment, Debugging, and Performance」コースに登録してください。

Security Best Practices in Google Cloud (Coursera)

https://www.coursera.org/learn/security-best-practices-in-google-cloud

This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

Security in Google Cloud (CourseraSpecs)

https://www.coursera.org/specializations/security-google-cloud-platform

Offered by Google Cloud. Launch your career in Cloud Security. This self-paced Specialization gives a broad study of security controls, best ...

Security in Google Cloud en Français (CourseraSpecs)

https://www.coursera.org/specializations/security-google-cloud-platform-fr

Offered by Google Cloud. Lancez votre carrière dans la Cloud Security. Cette spécialisation à votre rythme offre une étude approfondie des ...

Security in Google Cloud 日本語版 (CourseraSpecs)

https://www.coursera.org/specializations/security-google-cloud-platform-ja

Offered by Google Cloud. クラウドセキュリティでキャリアをスタート. このセルフペースのスペシャライゼーションは、Google Cloudのセキュリティ管理、ベストプラクティス、テクニックに関する幅広い調査を提供します。

Serverless Data Analysis with Google BigQuery and Cloud Dataflow em Português Brasileiro (Coursera)

https://www.coursera.org/learn/serverless-data-analysis-bigquery-cloud-dataflow-gcp-br

Este curso rápido sob demanda tem uma semana de duração e é baseado no Google Cloud Platform Big Data and Machine Learning Fundamentals. Por meio de apresentações com instrutores, demonstrações e laboratórios práticos, os alunos aprenderão a executar armazenamento de dados, análise e processamento de pipeline em um ambiente autônomo. Pré-requisitos: • Noções básicas de Big Data e Machine Learning do Google Cloud Platform • Experiência no uso de uma linguagem de consulta semelhante a SQL par

Serverless Data Processing Dataflow em Português Brasileiro (CourseraSpecs)

https://www.coursera.org/specializations/serverless-data-processing-with-dataflow-pt

Offered by Google Cloud. Criando aplicativos de Big Data que escalam

Serverless Data Processing with Dataflow (CourseraSpecs)

https://www.coursera.org/specializations/serverless-data-processing-with-dataflow

Offered by Google Cloud. Building Big Data Applications that Scale

Serverless Data Processing with Dataflow en Español (CourseraSpecs)

https://www.coursera.org/specializations/serverless-data-processing-with-dataflow-es

Offered by Google Cloud. Creación de aplicaciones de Big Data escalables

Serverless Data Processing with Dataflow: Develop Pipelines (Coursera)

https://www.coursera.org/learn/developing-pipelines-on-dataflow

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 p

Serverless Data Processing with Dataflow: Foundations (Coursera)

https://www.coursera.org/learn/serverless-data-processing-with-dataflow-foundations

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 compu

Serverless Data Processing with Dataflow: Operations (Coursera)

https://www.coursera.org/learn/serverless-data-processing-with-dataflow-operations

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platfor

Serverless Machine Learning with Tensorflow on Google Cloud em Português Brasileiro (Coursera)

https://www.coursera.org/learn/serverless-machine-learning-gcp-br

Este curso intensivo sob demanda de quatro dias oferece aos participantes uma introdução sobre como projetar e criar sistemas de machine learning no Google Cloud Platform. Por meio de apresentações, demonstrações e laboratórios práticos, os participantes aprenderão os conceitos de machine learning (ML) e do TensorFlow, além de habilidades de desenvolvimento, avaliação e produção de modelos de ML. OBJETIVOS Neste curso, os participantes aprenderão as seguintes habilidades: ● Identificar

Site Reliability Engineering: Measuring and Managing Reliability (Coursera)

https://www.coursera.org/learn/site-reliability-engineering-slos

Service level indicators (SLIs) and service level objectives (SLOs) are fundamental tools for measuring and managing reliability. In this course, students learn approaches for devising appropriate SLIs and SLOs and managing reliability through the use of an error budget.