Coursera

Google Cloud Big Data and Machine Learning Fundamentals en Español (Coursera)

Offered by Google Cloud,
Google Cloud Big Data and Machine Learning Fundamentals en Español (Coursera)

En este curso a pedido y acelerado de 1 semana, los participantes descubrirán las capacidades de los macrodatos y del aprendizaje automático de Google Cloud Platform (GCP). Además, se proporciona una descripción general rápida de Google Cloud Platform y más detalles sobre las capacidades de procesamiento de datos.

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

Al finalizar este curso, los participantes podrán hacer lo siguiente:
• Identificar el propósito y el valor de los productos clave de macrodatos y aprendizaje automático disponibles en Google Cloud Platform
• Usar Cloud SQL y Cloud Dataproc para migrar las cargas de trabajo existentes de MySQL y Hadoop/Pig/Spark/Hive a Google Cloud Platform
• Usar BigQuery y Cloud Datalab para llevar a cabo un análisis de datos interactivo
• Elegir entre Cloud SQL, Bigtable y Datastore
• Entrenar y usar una red neuronal mediante TensorFlow
• Elegir entre los diferentes productos de procesamiento de datos disponibles en Google Cloud Platform
Antes de inscribirse en este curso, los participantes deben tener aproximadamente un (1) año de experiencia en uno o más de los siguientes:
• Un lenguaje de consulta común, como SQL
• Actividades de extracción, transformación y carga
• Modelado de datos
• Aprendizaje automático o estadísticas
• Programación en Python
Notas de la Cuenta de Google:
• Actualmente, los servicios de Google no están disponibles en China.
This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

Syllabus

WEEK 1
Introducción al programa de especialización Data Engineering, Big Data, and Machine Learning on GCP
Le damos la bienvenida al curso Google Cloud Platform Big Data and Machine Learning Fundamentals. Aquí obtendrá información básica sobre cómo está estructurado el curso y los cuatro desafíos principales relacionados con los macrodatos que deberá superar.

WEEK 2
Recomendación de productos con Cloud SQL y Spark
En este módulo, tendrá un modelo de recomendación existente de Apache Spark ML que se ejecuta de manera local. Aprenderá acerca de los modelos de recomendación y cómo puede ejecutarlos en la nube con Cloud Dataproc y Cloud SQL.

WEEK 3
Prediga las compras de visitantes con BigQuery ML
En este módulo, aprenderá los conceptos básicos de BigQuery y del análisis de macrodatos a gran escala. Luego, aprenderá a compilar su propio modelo personalizado de aprendizaje automático para predecir las compras de visitantes usando solamente SQL con BigQuery ML.

WEEK 4
Cree canalizaciones de datos de transmisión con Cloud Pub/Sub y Cloud Dataflow+
En este módulo, diseñará y compilará una canalización de datos de transmisión con ajuste de escala automático para transferir, procesar y visualizar datos en un panel. Antes de compilar su canalización, aprenderá los conceptos básicos de la arquitectura orientada a los mensajes y los errores que debe evitar al diseñar y al implementar canalizaciones de datos modernas.

WEEK 5
Clasifique imágenes con modelos previamente compilados mediante la API de Vision y Cloud AutoML
¿No quiere crear un modelo personalizado de AA desde cero? Aprenda a aprovechar y extender los modelos de AA previamente compilados, como la API de Vision y Cloud AutoML, para la clasificación de imágenes.

WEEK 6
Resumen
En este último módulo, revisaremos los desafíos clave, las soluciones y los temas abordados como parte de este curso sobre aspectos básicos. También revisaremos los recursos adicionales y los pasos que puede seguir para obtener la certificación Data Engineer de Google Cloud.

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)

Data Science

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 22nd 2026
5-12 Weeks
Machine Learning Data Science APIs
Details
Relational Database Support for Data Warehouses (Coursera) Coursera
University of Colorado System

Relational Database Support for Data Warehouses (Coursera)

Statistics & Data Analysis Data Science

Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization. In this course, you'll use analytical elements of SQL for answering business intelligence questions. You'll learn features of relational database management systems for managing summary data commonly used in business intelligence reporting. Because of the importance and difficulty of managing implementations of data warehouses, we'll also delve into storage architectures, scalable parallel processing, data governance, and big data impacts. In the assignments in this course, you can use either Oracle or PostgreSQL.

Jun 22nd 2026
5-12 Weeks
Databases SQL Big Data
Details
The Importance of Listening (Coursera) Coursera
Northwestern University

The Importance of Listening (Coursera)

Marketing & Communication Business

In this second MOOC in the Social Marketing Specialization - "The Importance of Listening" - you will go deep into the Big Data of social and gain a more complete picture of what can be learned from interactions on social sites. You will be amazed at just how much information can be extracted from a single post, picture, or video.

Jun 22nd 2026
4 Weeks
Marketing Big Data Social Media
Details
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera)

Security & Networking

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information.

Jun 22nd 2026
4 Weeks
Cloud Machine Learning Big Data
Details
Machine Learning With Big Data (Coursera) Coursera
University of California, San Diego

Machine Learning With Big Data (Coursera)

Statistics & Data Analysis Data Science

Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.

Jun 22nd 2026
5-12 Weeks
Algorithms Machine Learning Big Data
Details
Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera) Coursera
University of Minnesota

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

Data Science

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 22nd 2026
4 Weeks
Statistics Machine Learning Data Mining
Details
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

Statistics & Data Analysis Data Science

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Jun 22nd 2026
4 Weeks
Programming Python Machine Learning
Details
Browser-based Models with TensorFlow.js (Coursera) Coursera
DeepLearning.AI

Browser-based Models with TensorFlow.js (Coursera)

CS: Software Engineering Computer Science

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this first course, you’ll train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam.

Jun 22nd 2026
4 Weeks
Machine Learning Object Detection TensorFlow
Details
Practical Predictive Analytics: Models and Methods (Coursera) Coursera
University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistics & Data Analysis Data Science

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.

Jun 22nd 2026
4 Weeks
Machine Learning Models Methods
Details
Managing Big Data with MySQL (Coursera) Coursera
Duke University

Managing Big Data with MySQL (Coursera)

Statistics & Data Analysis Data Science

This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts.

Jun 22nd 2026
5-12 Weeks
Databases SQL Big Data
Details