Develop Your Google Cloud Network
Earned juil. 18, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned mai 11, 2024 EDT
Getting Started with Terraform for Google Cloud
Earned avr. 6, 2024 EDT
Logging and Monitoring in Google Cloud
Earned mars 31, 2024 EDT
Getting Started with Google Kubernetes Engine
Earned mars 26, 2024 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned mars 24, 2024 EDT
Essential Google Cloud Infrastructure: Core Services
Earned mars 20, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned mars 14, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned fév. 20, 2024 EST
Introduction to AI and Machine Learning on Google Cloud
Earned nov. 7, 2023 EST
This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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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.
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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.
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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.
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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.
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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure.
Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
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This course teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud.
Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
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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. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.
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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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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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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. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.
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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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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
Introduction to Image Generation
Earned août 31, 2025 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned août 21, 2025 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned juin 26, 2025 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned juil. 18, 2024 EDT
Develop Your Google Cloud Network
Earned juil. 18, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned mai 11, 2024 EDT
Getting Started with Terraform for Google Cloud
Earned avr. 6, 2024 EDT
Logging and Monitoring in Google Cloud
Earned mars 31, 2024 EDT
Getting Started with Google Kubernetes Engine
Earned mars 26, 2024 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned mars 24, 2024 EDT
Essential Google Cloud Infrastructure: Core Services
Earned mars 20, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned mars 14, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned fév. 20, 2024 EST
Introduction to AI and Machine Learning on Google Cloud
Earned nov. 7, 2023 EST