Sukesh Naga
Date d'abonnement : 2022
Ligue de Diamant
13190 points
Create Image Captioning Models
Earned juil. 10, 2024 EDT
Transformer Models and BERT Model
Earned juil. 10, 2024 EDT
Encoder-Decoder Architecture
Earned juil. 10, 2024 EDT
Attention Mechanism
Earned juil. 10, 2024 EDT
Generative AI for Business Leaders
Earned juil. 1, 2024 EDT
[DEPRECATED] App Dev with Gemini
Earned juin 27, 2024 EDT
[DEPRECATED] Implementing Generative AI with Vertex AI
Earned juin 27, 2024 EDT
[DEPRECATED] - Multimodality with Gemini
Earned juin 18, 2024 EDT
Introduction to Vertex AI Studio
Earned juin 17, 2024 EDT
[DEPRECATED] Getting Started with the Vertex AI Gemini API
Earned juin 17, 2024 EDT
Generative AI Explorer : Vertex AI
Earned juin 14, 2024 EDT
Google Cloud Essentials
Earned mai 17, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned sept. 1, 2023 EDT
Generative AI Fundamentals
Earned sept. 1, 2023 EDT
[DEPRECATED]Introduction to Responsible AI
Earned sept. 1, 2023 EDT
Introduction to Large Language Models
Earned sept. 1, 2023 EDT
Introduction to Generative AI
Earned sept. 1, 2023 EDT
Technical Onboarding Checklist Certification Quest
Earned août 16, 2023 EDT
Cloud Foundations: Customer Onboarding Best Practices
Earned juin 7, 2023 EDT
Getting Started with Google Kubernetes Engine
Earned juil. 8, 2022 EDT
Admin Roles and Folder Access
Earned juin 3, 2022 EDT
Version Control and Caching
Earned juin 2, 2022 EDT
The Modern Data Platform and LookML
Earned juin 1, 2022 EDT
Document AI
Earned mars 25, 2022 EDT
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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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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Unlock the power of Google Cloud's cutting-edge Vertex AI Gemini API to craft innovative multimodal applications. This hands-on course delves into the integration of the Vertex AI SDK for Python, guiding you through the generation of sophisticated responses powered by the Gemini Pro and Gemini Pro Vision models. Get ready to build, deploy, and harness the transformative capabilities of multimodal AI within your own projects.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
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Delve into the power of multimodal AI with this project-based course using Gemini. Master essential techniques and build advanced applications. You will:
- Experiment with multimodal use cases to expand application possibilities
- Implement recommendation systems that combine suggestions with clear reasoning
- Design a powerful document search engine using multimodal RAG methods
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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Get hands-on with the Gemini Pro and Gemini Pro Vision models through our new labs. This course gives you a unique chance to explore these powerful AI tools while our training content is still in development. Learn to interact with the models using the Vertex AI Gemini API and cURL commands, and help us create the best possible learning experience around this technology.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
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This content is deprecated. Please see the latest version of the course, here.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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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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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 3 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. Explore other content in the Gemini Agent Ready (GEAR) program.
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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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This quest comprises a series of Challenge and Learning labs aimed at validating your proficiency in setting up a Google Cloud organization for scalable, production-ready, enterprise workloads.
Each lab is structured around the Google Cloud setup checklist, which provides administrators with complete control over a company's Google Cloud resources. The checklist comprises 10 items, and each item includes step-by-step procedures that outline a recommended path to follow. Although there may be multiple ways to complete some tasks, it's important to keep track of your choices if you don't follow the recommended path.
In the Challenge Labs, you'll be given a set of tasks that you must complete on your own with minimal assistance. An automated scoring system will provide feedback on whether you have successfully completed your tasks.
The Learning Labs will provide you with step-by-step instructions on how to perform the required tasks. However, due to limitations imposed by the Qwik…
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The Cloud Foundations Customer Onboarding: Best Practices course enables partners to onboard customers on Google Cloud efficiently and in minimum time, by imparting knowledge, IP, and best practices from the Technical Onboarding Center (TOC) team at Global Delivery Center (GDC). The course explores Cloud Identity and organization, users and groups, administrative access, and resource hierarchy. It also examines network configuration, hybrid connectivity, logging and monitoring, and organizational security.
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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 is designed to teach you about roles, permission sets and model sets. These are areas that are used together to manage what users can do and what they can see in Looker.
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This course aims to introduce you to the basic concepts of Git: what it is and how it's used in Looker. You will also develop an in-depth knowledge of the caching process on the Looker platform, such as why they are used and why they work
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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.
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This course provides partners the skills required to scope, design and deploy Document AI solutions for enterprise customers utilizing use-cases from both the procurement and lending arenas.
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