Develop your Google Cloud Network
Earned sept. 12, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned août 13, 2024 EDT
Implement Load Balancing on Compute Engine
Earned août 8, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned juil. 10, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned jan. 22, 2024 EST
Enterprise Search on Generative AI App Builder
Earned jan. 22, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned jan. 21, 2024 EST
Introduction to Vertex AI Studio
Earned jan. 20, 2024 EST
Create Image Captioning Models
Earned jan. 20, 2024 EST
Transformer Models and BERT Model
Earned jan. 20, 2024 EST
Encoder-Decoder Architecture
Earned jan. 20, 2024 EST
Attention Mechanism
Earned jan. 20, 2024 EST
Introduction to Image Generation
Earned jan. 20, 2024 EST
Generative AI Fundamentals
Earned jan. 20, 2024 EST
Introduction to Responsible AI
Earned jan. 20, 2024 EST
Introduction to Large Language Models
Earned jan. 20, 2024 EST
Introduction to Generative AI
Earned jan. 20, 2024 EST
Getting Started with Google Kubernetes Engine
Earned juin 21, 2022 EDT
Reliable Google Cloud Infrastructure: Design and Process
Earned juin 20, 2022 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned juin 19, 2022 EDT
Essential Google Cloud Infrastructure: Foundation
Earned juin 19, 2022 EDT
Essential Google Cloud Infrastructure: Core Services
Earned juin 18, 2022 EDT
Earn a skill badge by completing the Develop your Google Cloud Network course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM rols 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. A skill badge is an exclusivedigital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the introductory Implement Load Balancing on Compute Engine skill badge to demonstrate skills in the following: writing gcloud commands and using Cloud Shell, creating and deploying virtual machines in Compute Engine, and configuring network and HTTP load balancers. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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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 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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Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use Generative AI App Builder to integrate enterprise-grade generative AI search.
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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 interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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This course introduces Vertex AI Studio, a tool for prototyping and customizing generative AI models. Through immersive lessons, engaging demos, and a hands-on lab, you'll explore the generative AI workflow and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, and model tuning. The aim is to enable you to unlock the potentials of these models in your projects with Vertex AI Studio.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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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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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 7 AI principles.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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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 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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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, 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.
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.
Develop your Google Cloud Network
Earned sept. 12, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned août 13, 2024 EDT
Implement Load Balancing on Compute Engine
Earned août 8, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned juil. 10, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned jan. 22, 2024 EST
Enterprise Search on Generative AI App Builder
Earned jan. 22, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned jan. 21, 2024 EST
Introduction to Vertex AI Studio
Earned jan. 20, 2024 EST
Create Image Captioning Models
Earned jan. 20, 2024 EST
Transformer Models and BERT Model
Earned jan. 20, 2024 EST
Encoder-Decoder Architecture
Earned jan. 20, 2024 EST
Attention Mechanism
Earned jan. 20, 2024 EST
Introduction to Image Generation
Earned jan. 20, 2024 EST
Generative AI Fundamentals
Earned jan. 20, 2024 EST
Introduction to Responsible AI
Earned jan. 20, 2024 EST
Introduction to Large Language Models
Earned jan. 20, 2024 EST
Introduction to Generative AI
Earned jan. 20, 2024 EST
Getting Started with Google Kubernetes Engine
Earned juin 21, 2022 EDT
Reliable Google Cloud Infrastructure: Design and Process
Earned juin 20, 2022 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned juin 19, 2022 EDT
Essential Google Cloud Infrastructure: Foundation
Earned juin 19, 2022 EDT
Essential Google Cloud Infrastructure: Core Services
Earned juin 18, 2022 EDT