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Justo Lins Joao Marcos

メンバー加入日: 2024

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11470 ポイント
Generative AI for Business Leaders Earned 11月 14, 2024 EST
Introduction to Security in the World of AI Earned 10月 29, 2024 EDT
Jump Start and Duet AI Earned 10月 28, 2024 EDT
生成 AI のための ML オペレーション（MLOps) Earned 10月 28, 2024 EDT
Creating a Customizable Digital Assistant Earned 10月 25, 2024 EDT
Using Generative AI to Enhance Contact Center AI Solutions Earned 10月 25, 2024 EDT
Generative AI for Marketing Earned 10月 24, 2024 EDT
Upgrading your skills to work with Generative AI Earned 10月 24, 2024 EDT
Scale AI with Ray on Vertex AI Earned 10月 24, 2024 EDT
Generative AI in Google Cloud Databases Earned 10月 24, 2024 EDT
Generative AI Fundamentals Earned 10月 22, 2024 EDT
Enterprise Readiness in Generative AI Earned 10月 22, 2024 EDT
責任ある AI の概要 Earned 10月 22, 2024 EDT
Generative AI Assisted Development Earned 10月 22, 2024 EDT
Experimenting and Evaluating your Gen AI models Earned 10月 16, 2024 EDT
Building AI with Colab Enterprise Earned 10月 15, 2024 EDT
大規模言語モデルの概要 Earned 10月 15, 2024 EDT
生成 AI の概要 Earned 10月 15, 2024 EDT

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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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.

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With a focus on developer pain points, explore how to get started with a new cloud with Jump-Start solutions. Discover one-click generative AI deployment, and the benefits of interactive learning, cost viability and architecture best practices. Explore the available Jump Start solutions and Duet AI features. And, use Duet AI and Python to share results stored in the cloud. Generate code, commands, unit tests, citations and summarize code.

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このコースでは、生成 AI モデルのデプロイと管理において MLOps チームが直面する特有の課題に対処するために必要な知識とツールを提供し、AI チームが MLOps プロセスを合理化して生成 AI プロジェクトを成功させるうえで Vertex AI がどのように役立つかを説明します。

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Craft, deploy, and manage bots and AI models in Vertex AI. Unlock customer service and product management automation.

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In this course, you will learn about the four broad pillars of Google's Contact Center AI (CCAI), Virtual Agents, Agent Assist, Insights and CCAIP. You will explore the new generative AI features for Dialogflow CX, Agent Assist and Insights. And, you will learn how to leverage the Contact Center AI (CCAI) platform to transform your contact center with choice and flexibility.

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Leverage Google Cloud and generative AI to build powerful marketing apps and analyze data effectively.

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Learn about the new skills you'll need to be successful when using generative AI. Google Cloud has used generative AI to help keep you engaged and streamline your learning journey.

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In this course, you will learn how to easily scale AI from laptop to Cloud by bringing Ray and Vertex AI together. You will learn how to create a Ray cluster, connect to it, and run some simple Ray code. You will also learn how to integrate BigQuery seamlessly with Ray data.

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This course introduces the new generative AI features for Google Cloud databases, including Alloy DB AI, and Duet AI for the Database Migration Service. You will discover how generative AI can be implemented at the orchestration layer and explore various orchestration scenarios. You will also find out how Google Cloud uses Duet AI with databases.

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Earn a skill badge 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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Explore the four pillars of Enterprise Readiness in generative AI: data governance and privacy, security and compliance support, infrastructure reliability and sustainability, and responsible AI. You will also learn how these pillars address concerns about data privacy and security. Learn about customizing foundation models with your data while keeping your data safe using adapter layers, how to keep your AI models safe and compliant when deploying them across the world, and the multiple layers of encryption, rigorous controls, supply chain audits, and ongoing security testing that are built into Google Cloud. You will also learn about security controls such as VPC, customer-managed encryption keys, access transparency, and data residency zones. And explore enterprise controls, certifications, and responsible AI tooling available in Vertex AI to ensure your data remains secure and compliant with global regulations when deploying generative AI models.

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この入門レベルのマイクロラーニング コースでは、責任ある AI の概要と重要性、および Google が責任ある AI を自社プロダクトにどのように実装しているのかについて説明します。また、Google の AI に関する 7 つの原則についても説明します。

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Discover how to integrate AI assistance for developers, to support AI code completion, explaining code, unit tests and IP compliance. AI assisted no code development with prompt driven app creation through Duet AI in AppSheet. Duet AI is available for multiple IDEs via Cloud Code. Explore use cases that answer the question ‘How can AI help solve productivity blockers?’ Explore code completion and generation, code license attribution, code explanation, unit tests and foundation models with Duet AI. A demonstration of developing a Kubernetes application with Duet AI in Cloud Code.

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Model experimentation and evaluation are critical steps in the journey to productionalize an LLM. This course introduces new tools that will help simplify these tasks.

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Discover how to use Colab Enterprise, a managed notebook environment that provides secure and compliant storage for your notebooks, that comes with two code-generation features: code complete and code gen. Create and use runtime templates in Vertex AI Workbench to give users access to more powerful compute resources while still maintaining control over the types of resources that are spun up. Share notebooks with other users and use versioning to keep track of changes to your notebooks. Learn how Colab Enterprise integrates BigQuery and Vertex AI. You will see how to pull data from BigQuery, use BQML to train a model, and have it all integrated with Vertex Model Registry. Explore how to fine-tune a Foundation model or generative AI model using the Vertex AI SDK. And, learn how to evaluate a tuned model and compare the results of multiple runs.

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このコースは、大規模言語モデル（LLM）とは何か、どのようなユースケースで活用できるのか、プロンプトのチューニングで LLM のパフォーマンスを高めるにはどうすればよいかについて学習する、入門レベルのマイクロ ラーニング コースです。独自の生成 AI アプリを開発する際に利用できる Google ツールも紹介します。

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この入門レベルのマイクロラーニング コースでは、生成 AI の概要、利用方法、従来の機械学習の手法との違いについて説明します。独自の生成 AI アプリを作成する際に利用できる Google ツールも紹介します。

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