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NAGARAJ KINI

Date d'abonnement : 2022

Ligue de Diamant

22230 points
Preparing for Your Associate Cloud Engineer Journey Earned mars 3, 2025 EST
Customer Engagement Suite with Google AI Architecture Earned juil. 14, 2024 EDT
Manage Functions and Reporting with CCAIP Earned juil. 6, 2024 EDT
Handle Consumer Interactions with CCAIP Earned juil. 3, 2024 EDT
Intro to Conversational AI and Conversational AI Engagement Framework Earned juin 30, 2024 EDT
MySQL to Cloud SQL Earned juin 30, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned juin 30, 2024 EDT
Selling the Platform & Building Client Trust Earned juin 30, 2024 EDT
Data Warehousing for Partners: Optimize in BigQuery Earned juin 30, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners Earned juin 30, 2024 EDT
Data Warehousing for Partners: Design in BigQuery Earned juin 29, 2024 EDT
Implementing Generative AI with Vertex AI Earned juin 24, 2024 EDT
Introduction to Large Language Models Earned juin 22, 2024 EDT
Data Warehousing for Partners: Enable Google Cloud Customers Earned juin 22, 2024 EDT
Create Image Captioning Models Earned juin 22, 2024 EDT
Transformer Models and BERT Model Earned juin 22, 2024 EDT
Encoder-Decoder Architecture Earned juin 22, 2024 EDT
Attention Mechanism Earned juin 21, 2024 EDT
Generative AI Fundamentals Earned juin 21, 2024 EDT

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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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.

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Manage Functions and Reporting with CCAI Platform provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCAI Platform.

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This course teaches contact center agents about the core agent features and functionality in Contact Center AI Platform (CCAIP). CCAIP is a unified contact center platform that accelerates an organization's ability to leverage and deploy CCAI without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.

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This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.

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Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.

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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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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities, learn to identify high-impact use cases, and develop the skills to demonstrate and integrate these technologies seamlessly into client solutions and operations.

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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.

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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases.

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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.

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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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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 course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.

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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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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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