Google Cloud Product Fundamentals en Español (Coursera)

Offered by Google Cloud,
Google Cloud Product Fundamentals en Español (Coursera)

Este curso, que es una continuación de Business Transformation with Google Cloud, le permitirá conocer la perspectiva tecnológica de la transformación de una organización. Para ser más específicos, explicaremos cómo la tecnología de Google Cloud puede transformar digitalmente una organización en los siguientes aspectos: modernizar la infraestructura de TI; mejorar la forma en que los equipos desarrollan las aplicaciones que utiliza la empresa; saber cómo aprovechar el aprendizaje automático y la inteligencia artificial para generar más valor; advertir el rol fundamental de las herramientas de productividad basadas en la nube, como G Suite, para cumplir con el trabajo, y comprender los desafíos y las oportunidades de la administración de costos que trae aparejados una infraestructura de TI cambiante basada en la nube.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

En el desarrollo del curso, explicaremos conceptos clave, como procesamiento, aplicaciones, seguridad, API, bases de datos, y sus funciones en la transformación digital. Además, conocerá ejemplos específicos del uso de diferentes tecnologías de nube y los beneficios que obtuvieron las personas y las empresas a nivel mundial. Más importante aún, le proporcionaremos el conocimiento necesario para contribuir en proyectos de transformación digital, o dirigirlos, y colaborar con las partes interesadas correctas.

What You Will Learn

  • Describe some of the key ways an organization can modernize its infrastructure modernization with Google Cloud technology.
  • Explain Google Cloud's recommended patterns for modernizing and developing applications and how Google Cloud Platform services can help.
  • Explain what is meant by the term "machine learning" and identify good use cases for it.
  • Explain the common challenges when it comes to cloud cost management and recommended best practices to address these challenges.

Syllabus

WEEK 1
Bienvenido a Google Cloud Product Fundamentals
En este módulo, conocerá a su primer instructor, aprenderá sobre la estructura del curso y obtendrá una descripción general del contenido de los módulos siguientes.

WEEK 2
Módulo 1: Cómo modernizar la infraestructura de TI con Google Cloud Platform (GCP)
En este módulo, se analiza la importancia de modernizar la infraestructura de TI de una empresa tradicional y las distintas formas en que los profesionales comerciales pueden utilizar los proveedores de servicios de la nube pública para lograr sus objetivos. Además, se explica cómo Google Cloud Platform (GCP) aborda las inquietudes comunes sobre la seguridad cibernética, y se describen algunas de las soluciones de procesamiento de GCP y la manera en que aportan valor a una organización.

WEEK 3
Módulo 2: Cómo compilar aplicaciones con Google Cloud Platform (GCP)
En el módulo anterior, se analizó la modernización de la infraestructura con GCP. En este módulo, se explora la modernización y compilación de aplicaciones con GCP. Las aplicaciones necesitan datos, por lo que también se analizarán los aspectos fundamentales del almacenamiento de datos y los distintos servicios de almacenamiento y base de datos que ofrece GCP.

WEEK 4
Módulo 3: Cómo transformar una empresa con inteligencia artificial y aprendizaje automático
En este módulo, se explora el significado del término "aprendizaje automático". Se analiza la función de los datos para entrenar los modelos de aprendizaje automático y los requisitos de los datos de calidad. Además, se observan casos prácticos comunes de aprendizaje automático en las distintas industrias. Por último, se explica cómo GCP puede ayudarlo con sus proyectos de aprendizaje automático.

WEEK 5
Módulo 4: Cómo transformar la manera en que se realiza el trabajo
Las herramientas heredadas limitan la capacidad colaborativa de las personas. En este módulo, se analiza por qué la colaboración transforma tanto la forma en que trabajan las personas y se explora por qué G Suite puede ayudar a fomentar una cultura colaborativa en una organización. Por último, en este módulo, se describe el impacto de G Suite en la organización a nivel individual y general con ejemplos de la industria.

WEEK 6
Módulo 5: Cómo comprender la administración de costos en la nube
La planificación financiera y los procedimientos de administración de costos pueden cambiar cuando una organización pasa de una infraestructura de TI local a una basada en la nube, o de proveedores de servicios en una nube a múltiples nubes. En este módulo, se analizan los cambios fundamentales; entre ellos, cómo considerar el costo total de propiedad de su TI en distintas situaciones. Por último, se exploran las prácticas recomendadas de GCP para administrar de manera eficaz los costos en la nube.

WEEK 7
Resumen
Conozca otros cursos, recursos y servicios profesionales de Google Cloud que puede aprovechar.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Getting started with TensorFlow 2 (Coursera) Coursera
Imperial College London

Getting started with TensorFlow 2 (Coursera)

Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models.

Jun 8th 2026
5-12 Weeks
Neural Networks and Deep Learning (Coursera) Coursera
DeepLearning.AI

Neural Networks and Deep Learning (Coursera)

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning.

Jun 8th 2026
4 Weeks
Interfacing with the Raspberry Pi (Coursera) Coursera
University of California, Irvine

Interfacing with the Raspberry Pi (Coursera)

The Raspberry Pi uses a variety of input/output devices based on protocols such as HDMI, USB, and Ethernet to communicate with the outside world. In this class you will learn how to use these protocols with other external devices (sensors, motors, GPS, orientation, LCD screens etc.) to get your IoT device to interact with the real world.

Jun 8th 2026
4 Weeks
Probabilistic Graphical Models 1: Representation (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 1: Representation (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Jun 8th 2026
5-12 Weeks
Machine Learning: Clustering & Retrieval (Coursera) Coursera
University of Washington

Machine Learning: Clustering & Retrieval (Coursera)

Case Studies: Finding Similar Documents. A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover?

Jun 8th 2026
5-12 Weeks
Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Jun 8th 2026
5-12 Weeks
AWS Cloud Technical Essentials (Coursera) Coursera
AWS

AWS Cloud Technical Essentials (Coursera)

Are you in a technical role and want to learn the fundamentals of AWS? Do you aspire to have a job or career as a cloud developer, architect, or in an operations role? If so, AWS Cloud Technical Essentials is an ideal way to start. This course was designed for those at the beginning of their cloud-learning journey - no prior knowledge of cloud computing or AWS products and services required!

Jun 9th 2026
5-12 Weeks
The Unix Workbench (Coursera) Coursera
Johns Hopkins University

The Unix Workbench (Coursera)

Unix forms a foundation that is often very helpful for accomplishing other goals you might have for you and your computer, whether that goal is running a business, writing a book, curing disease, or creating the next great app. The means to these goals are sometimes carried out by writing software. Software can’t be mined out of the ground, nor can software seeds be planted in spring to harvest by autumn. Software isn’t produced in factories on an assembly line. Software is a hand-made, often bespoke good. If a software developer is an artisan, then Unix is their workbench.

Jun 8th 2026
4 Weeks
Code Free Data Science (Coursera) Coursera
University of California, San Diego

Code Free Data Science (Coursera)

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Jun 8th 2026
4 Weeks
Practical Machine Learning (Coursera) Coursera
Johns Hopkins University

Practical Machine Learning (Coursera)

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates.

Jun 8th 2026
4 Weeks
Machine Learning Foundations: A Case Study Approach (Coursera) Coursera
University of Washington

Machine Learning Foundations: A Case Study Approach (Coursera)

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Jun 8th 2026
5-12 Weeks
Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera) Coursera
University of Minnesota

Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera)

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.

Jun 8th 2026
4 Weeks