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Architecting with Google Kubernetes Engine: Production
In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE. This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Getting Started with Google Kubernetes Engine
Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Google Cloud Fundamentals: Core Infrastructure
Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Architecting with Google Kubernetes Engine: Foundations
In this course, "Architecting with Google Kubernetes Engine: Foundations," you get a review of the layout and principles of Google Cloud, followed by an introduction to creating and managing software containers and an introduction to the architecture of Kubernetes.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Google Cloud Big Data and Machine Learning Fundamentals
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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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Reliable Google Cloud Infrastructure: Design and 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 Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Smart Analytics, Machine Learning, and AI on Google Cloud
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
API Design and Fundamentals of Google Cloud's Apigee API Platform
In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn about how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Building Batch Data Pipelines on Google Cloud
Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Essential Google Cloud Infrastructure: Foundation
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.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Exploring and Preparing your Data with BigQuery
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Google Cloud IAM and Networking for AWS Professionals
This is the first course of a four-course series for cloud architects and engineers with existing AWS knowledge, and it compares Google Cloud and AWS solutions and guides professionals on their use. This course focuses on Identity and Access Management (IAM) and networking in Google Cloud. The learners apply the knowledge of access management and networking in AWS to explore the similarities and differences with access management and networking in Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
App Deployment, Debugging, and Performance
In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Preparing for the Google Cloud Professional Data Engineer Exam
The purpose of this course is to help those who are qualified develop confidence to attempt the exam, and to help those not yet qualified to develop their own plan for preparation.…
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Managing Security 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 Identity, Resource Manager, Cloud IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Essential Google Cloud Infrastructure: Core Services
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
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.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Modernizing Data Lakes and Data Warehouses with Google Cloud
The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. This is the first course of the Data Engineering on Google Cloud series.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Logging, Monitoring and Observability in Google Cloud
Learn how to monitor, troubleshoot, and improve your infrastructure and application performance. Guided by the principles of Site Reliability Engineering (SRE), this course features a combination of lectures, demos, hand…
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
Mitigating Security Vulnerabilities on Google Cloud
In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Elastic Google Cloud Infrastructure: Scaling and Automation
This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Building Scalable Java Microservices with Spring Boot and Spring Cloud
"Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud. You'll use Spring Cloud Config to manage your application's configuration. You'll send and receive messages with Pub/Sub and Spring Integration.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Securing and Integrating Components of your Application
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.\n\nCompleting one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
TensorFlow on Google Cloud
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Computer Vision Fundamentals with Google Cloud
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية