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Google Cloud Training
Este es un curso introductorio de microaprendizaje destinado a explicar qué es la IA generativa, cómo se utiliza y en qué se diferencia de los métodos de aprendizaje automático tradicionales. También abarca las herramientas de Google para ayudarte a desarrollar tus propias aplicaciones de IA generativa.
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What's inside
Syllabus
Introducción a la IA generativa
Este es un curso introductorio de microaprendizaje destinado a explicar qué es la IA generativa, cómo se utiliza y en qué se diferencia de los métodos de aprendizaje automático tradicionales. También abarca las herramientas de Google para ayudarte a desarrollar tus propias aplicaciones de IA generativa.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces learners to generative AI, which is highly relevant to the tech industry
Provides guidance on developing generative AI applications, which is valuable for hands-on learning
Covers fundamental concepts of generative AI, making it beginner-friendly
Taught by Google Cloud Training, which is well-recognized in the field of generative AI
Microlearning approach makes it accessible for busy individuals
Focuses on the practical applications of generative AI, ensuring relevance to industry needs
Save this course
Save Introduction to Generative AI - Español to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Generative AI - Español with these
activities:
Review foundational concepts of generative AI and machine learning
Show steps
Help you gain a solid understanding of the key concepts and algorithms upon which generative AI builds, giving you a stronger foundation for learning the advanced material in this course.
Show steps
-
Read through the introductory chapters of a book or online resource on the fundamentals of generative AI and machine learning.
-
Complete a few tutorials or exercises that demonstrate the basic concepts.
-
Review your notes and identify any areas where you have questions or need further clarification.
Brush up on machine learning
Show steps
Review fundamental concepts of machine learning to bolster your understanding before the course starts.
Browse courses on
Machine Learning
Show steps
-
Revisit basic concepts like supervised and unsupervised learning.
-
Review common machine learning algorithms, such as linear and logistic regression.
-
Practice solving simple machine learning problems using a programming language.
Attend webinars or meetups on generative AI
Show steps
Connect with professionals in the field and gain insights from industry experts.
Show steps
-
Identify upcoming webinars or meetups related to generative AI.
-
Register and actively participate in discussions.
-
Connect with speakers and attendees to expand your network.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore Google Cloud Generative AI tools
Show steps
Enhance your understanding by following guided tutorials and experimenting with practical examples.
Show steps
-
Dive into Google Cloud's Generative AI Platform documentation.
-
Follow hands-on tutorials on using AutoML Vision, AutoML Tables, and Cloud DALL-E API.
-
Experiment with different parameters and settings to observe their impact on AI outputs.
Code challenges on generative AI
Show steps
Strengthen your technical skills by practicing problem-solving and implementing generative AI algorithms.
Show steps
-
Find online coding challenges or create your own related to generative AI.
-
Solve the challenges using appropriate programming languages and libraries.
-
Review solutions and identify areas for improvement.
Join a study group for generative AI
Show steps
Engage with peers, exchange ideas, and reinforce your learning through collaborative discussions.
Show steps
-
Find or create a study group with fellow learners or colleagues.
-
Set regular meeting schedules and assign topics for discussion.
-
Take turns presenting, leading discussions, and providing feedback.
Build a generative AI app using Google Cloud
Show steps
Apply your knowledge and create a mini-project to reinforce your understanding of generative AI in practice.
Show steps
-
Choose a specific problem or use case for your app.
-
Design and implement a prototype using Google Cloud tools and APIs.
-
Deploy your app and collect feedback from users.
Blog or write articles about generative AI
Show steps
Solidify your understanding by explaining concepts and sharing your insights on generative AI.
Show steps
-
Choose a topic related to generative AI that you want to explore further.
-
Research and gather information from reputable sources.
-
Write and edit your blog post or article, clearly explaining the topic and providing examples.
Contribute to open-source generative AI projects
Show steps
Gain practical experience by collaborating on real-world generative AI projects and contributing to the community.
Show steps
-
Identify open-source generative AI projects that align with your interests.
-
Review the project documentation and identify areas where you can contribute.
-
Communicate with project maintainers and propose your contributions.
Review foundational concepts of generative AI and machine learning
Show steps
Help you gain a solid understanding of the key concepts and algorithms upon which generative AI builds, giving you a stronger foundation for learning the advanced material in this course.
Show steps
Show steps
Show steps
- Read through the introductory chapters of a book or online resource on the fundamentals of generative AI and machine learning.
- Complete a few tutorials or exercises that demonstrate the basic concepts.
- Review your notes and identify any areas where you have questions or need further clarification.
Brush up on machine learning
Show steps
Review fundamental concepts of machine learning to bolster your understanding before the course starts.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Revisit basic concepts like supervised and unsupervised learning.
- Review common machine learning algorithms, such as linear and logistic regression.
- Practice solving simple machine learning problems using a programming language.
Attend webinars or meetups on generative AI
Show steps
Connect with professionals in the field and gain insights from industry experts.
Show steps
Show steps
Show steps
- Identify upcoming webinars or meetups related to generative AI.
- Register and actively participate in discussions.
- Connect with speakers and attendees to expand your network.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore Google Cloud Generative AI tools
Show steps
Enhance your understanding by following guided tutorials and experimenting with practical examples.
Show steps
Show steps
Show steps
- Dive into Google Cloud's Generative AI Platform documentation.
- Follow hands-on tutorials on using AutoML Vision, AutoML Tables, and Cloud DALL-E API.
- Experiment with different parameters and settings to observe their impact on AI outputs.
Code challenges on generative AI
Show steps
Strengthen your technical skills by practicing problem-solving and implementing generative AI algorithms.
Show steps
Show steps
Show steps
- Find online coding challenges or create your own related to generative AI.
- Solve the challenges using appropriate programming languages and libraries.
- Review solutions and identify areas for improvement.
Join a study group for generative AI
Show steps
Engage with peers, exchange ideas, and reinforce your learning through collaborative discussions.
Show steps
Show steps
Show steps
- Find or create a study group with fellow learners or colleagues.
- Set regular meeting schedules and assign topics for discussion.
- Take turns presenting, leading discussions, and providing feedback.
Build a generative AI app using Google Cloud
Show steps
Apply your knowledge and create a mini-project to reinforce your understanding of generative AI in practice.
Show steps
Show steps
Show steps
- Choose a specific problem or use case for your app.
- Design and implement a prototype using Google Cloud tools and APIs.
- Deploy your app and collect feedback from users.
Blog or write articles about generative AI
Show steps
Solidify your understanding by explaining concepts and sharing your insights on generative AI.
Show steps
Show steps
Show steps
- Choose a topic related to generative AI that you want to explore further.
- Research and gather information from reputable sources.
- Write and edit your blog post or article, clearly explaining the topic and providing examples.
Contribute to open-source generative AI projects
Show steps
Gain practical experience by collaborating on real-world generative AI projects and contributing to the community.
Show steps
Show steps
Show steps
- Identify open-source generative AI projects that align with your interests.
- Review the project documentation and identify areas where you can contribute.
- Communicate with project maintainers and propose your contributions.
Career center
Learners who complete Introduction to Generative AI - Español will develop knowledge and skills
that may be useful to these careers:
Ingeniero de Aprendizaje Automático
Ingeniero de Aprendizaje Automático
Los ingenieros de aprendizaje automático desarrollan y mantienen sistemas de aprendizaje automático que se utilizan en una variedad de industrias. Este curso puede ser útil para los ingenieros de aprendizaje automático que deseen aprender más sobre la IA generativa y cómo utilizarla en sus propios proyectos.
Científico de datos
Científico de datos
Los científicos de datos utilizan el aprendizaje automático y otras técnicas para extraer conocimientos de los datos. Este curso puede ser útil para los científicos de datos que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus modelos.
Analista de negocios
Analista de negocios
Los analistas de negocios trabajan con las empresas para identificar y resolver problemas empresariales. Este curso puede ser útil para los analistas de negocios que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus procesos comerciales.
Desarrollador de software
Desarrollador de software
Los desarrolladores de software diseñan, desarrollan y mantienen aplicaciones de software. Este curso puede ser útil para los desarrolladores de software que deseen aprender más sobre la IA generativa y cómo utilizarla para crear nuevas aplicaciones innovadoras.
Diseñador de UX
Diseñador de UX
Los diseñadores de UX diseñan la interfaz de usuario de las aplicaciones y los sitios web. Este curso puede ser útil para los diseñadores de UX que deseen aprender más sobre la IA generativa y cómo utilizarla para crear interfaces de usuario más atractivas.
Gerente de Producto
Gerente de Producto
Los gerentes de producto trabajan con los equipos de ingeniería y diseño para crear nuevos productos y funciones. Este curso puede ser útil para los gerentes de producto que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus productos.
Investigador de Operaciones
Investigador de Operaciones
Los investigadores de operaciones utilizan técnicas matemáticas y analíticas para resolver problemas empresariales. Este curso puede ser útil para los investigadores de operaciones que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus modelos.
Estadístico
Estadístico
Los estadísticos recopilan, analizan e interpretan datos. Este curso puede ser útil para los estadísticos que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus modelos estadísticos.
Ingeniero de datos
Ingeniero de datos
Los ingenieros de datos diseñan, construyen y mantienen sistemas que almacenan y procesan datos. Este curso puede ser útil para los ingenieros de datos que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus sistemas de datos.
Arquitecto de Soluciones
Arquitecto de Soluciones
Los arquitectos de soluciones diseñan y desarrollan soluciones tecnológicas para las empresas. Este curso puede ser útil para los arquitectos de soluciones que deseen aprender más sobre la IA generativa y cómo utilizarla para crear soluciones más innovadoras.
Emprendedor
Emprendedor
Los emprendedores crean y dirigen sus propios negocios. Este curso puede ser útil para los emprendedores que deseen aprender más sobre la IA generativa y cómo utilizarla para crear nuevos productos y servicios innovadores.
Consultor de gestión
Consultor de gestión
Los consultores de gestión trabajan con las empresas para resolver problemas empresariales y mejorar su rendimiento. Este curso puede ser útil para los consultores de gestión que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar sus servicios de consultoría.
Profesor
Profesor
Los profesores enseñan e investigan en universidades y otras instituciones educativas. Este curso puede ser útil para los profesores que deseen aprender más sobre la IA generativa y cómo utilizarla para mejorar su enseñanza e investigación.
Estudiante
Estudiante
Los estudiantes están cursando un título en una universidad u otra institución educativa. Este curso puede ser útil para los estudiantes que deseen aprender más sobre la IA generativa y cómo utilizarla en sus estudios y futuros proyectos.
Investigador
Investigador
Los investigadores realizan investigaciones originales en una variedad de campos. Este curso puede ser útil para los investigadores que deseen aprender más sobre la IA generativa y cómo utilizarla en su investigación.
For more career information including salaries, visit:
OpenCourser.com/course/n7kmh9/introduction
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Generative AI - Español.
There are a number of great books that cover generative AI. These books are a great way to learn about the fundamentals of generative AI, and to get a deeper understanding of the different types of generative models.
Save
Comprehensive guide to deep learning. It covers the fundamentals of deep learning, including convolutional neural networks, recurrent neural networks, and transformers. It also discusses the challenges and opportunities of using deep learning in various domains.
This paper introduces variational autoencoders (VAEs). VAEs are a type of generative model that can be used to generate realistic images, videos, and music. They are also useful for unsupervised learning tasks, such as clustering and dimensionality reduction.
Focuses on the theoretical and practical aspects of generative deep learning models, providing a comprehensive overview of the field. It valuable resource for researchers and advanced practitioners interested in the latest advancements in generative AI.
Provides a practical guide to building and deploying real-world AI applications, covering the challenges and best practices involved in the development and implementation of AI solutions. It useful resource for understanding the practical aspects of generative AI.
Provides a comprehensive overview of probabilistic graphical models, which are a fundamental mathematical framework used in generative AI. It valuable resource for understanding the underlying theory and principles behind generative AI models.
Save
Provides a detailed overview of generative adversarial networks (GANs), which are a powerful class of generative AI models. It valuable resource for researchers and advanced practitioners interested in the theory and implementation of GANs.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/n7kmh9/introduction
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Effort
1 week of study, 6-8 hours
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Transcript
Español
Good to know
Introduces learners to generative AI, which is highly relevant to the tech industry
Provides guidance on developing generative AI applications, which is valuable for hands-on learning
Covers fundamental concepts of generative AI, making it beginner-friendly
Taught by Google Cloud Training, which is well-recognized in the field of generative AI
Microlearning approach makes it accessible for busy individuals
Focuses on the practical applications of generative AI, ensuring relevance to industry needs
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