Smart Analytics, Machine Learning, and AI on Google Cloud
Earned oct. 4, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned sept. 16, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned sept. 12, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned sept. 3, 2024 EDT
Set Up a Google Cloud Network
Earned juil. 22, 2023 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned juil. 7, 2023 EDT
Develop Your Google Cloud Network
Earned juin 22, 2023 EDT
Essential Google Cloud Infrastructure: Core Services
Earned juin 14, 2023 EDT
Set Up an App Dev Environment on Google Cloud
Earned juin 6, 2023 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned juin 3, 2023 EDT
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.
En savoir plus
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.
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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 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.
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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.
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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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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned oct. 4, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned sept. 16, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned sept. 12, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned sept. 3, 2024 EDT
Set Up a Google Cloud Network
Earned juil. 22, 2023 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned juil. 7, 2023 EDT
Develop Your Google Cloud Network
Earned juin 22, 2023 EDT
Essential Google Cloud Infrastructure: Core Services
Earned juin 14, 2023 EDT
Set Up an App Dev Environment on Google Cloud
Earned juin 6, 2023 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned juin 3, 2023 EDT