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Syllabus

Introducción
El curso consta de dos módulos: Flutter, Gemini y Vertex AI: Este es el primer módulo del curso, contiene cuatro lecciones que proporcionan una introducción para el módulo y una descripción general de la IA generativa y Gemini, Vertex AI y Flutter. IA generativa en Vertex AI: Este módulo consta de cinco lecciones que incluyen una introducción al módulo y lecciones en las que aprenderás sobre la IA generativa en Vertex AI, Vertex AI Agent Builder, Vertex AI Search y el uso de un agente de Reasoning Engine en aplicaciones de IA generativa.
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Activities

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Career center

Learners who complete Crea agentes basados en IA generativa con Vertex AI y Flutter will develop knowledge and skills that may be useful to these careers:

Reading list

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Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
Explores the potential impact of generative AI on society, discussing how it could be used to solve social problems and improve quality of life. It is written by Kai-Fu Lee, a leading researcher in the field.
Explores the potential impact of generative AI on the law, discussing how it could be used to automate legal processes and improve access to justice. It is written by Ryan Abbott, a leading researcher in the field.
Explores the philosophical implications of generative AI, discussing how it challenges our understanding of mind and consciousness. It is written by Daniel C. Dennett, a leading philosopher in the field.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Explores the potential applications of generative AI in climate change, discussing how it could be used to model climate change and develop solutions. It is written by Andrew Ng, a leading researcher in the field.
Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
Explores the relationship between generative AI and the creative process, discussing how generative AI can be used to enhance creativity. It is written by Margaret Boden, a leading researcher in the field.
Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
Explores the potential impact of generative AI on the economy, discussing how it could be used to create new jobs and improve productivity. It is written by two leading experts in the field, Erik Brynjolfsson and Andrew McAfee.
Provides a comprehensive overview of machine learning on Google Cloud Platform, including Vertex AI. It covers the fundamentals of machine learning, as well as how to build, train, and deploy models using Vertex AI.
Provides a collection of recipes for using Vertex AI. It covers a wide range of topics, from data preprocessing to model deployment. This book is especially valuable for beginners who want to get started with Vertex AI.
Provides a collection of recipes for solving common problems when developing Flutter applications.
Provides a comprehensive overview of Flutter and its features, including a discussion of how to use Flutter for building multi-platform applications.
Guide to designing and implementing low-code applications with Gemini, providing guidance on best practices and architecture.
Classic introduction to reinforcement learning, covering topics such as Markov decision processes, value functions, and Q-learning. It valuable resource for anyone who wants to learn about reinforcement learning.
Comprehensive guide to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It must-read for anyone who wants to learn about deep learning.
Provides a gentle introduction to machine learning, focusing on the most important concepts and algorithms. It good choice for readers who are new to the field.
Provides a comprehensive overview of AI, covering topics such as machine learning, natural language processing, and computer vision. It is also written in a clear and concise style, making it accessible to readers of all levels.

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