Coursera

Serverless Data Processing with Dataflow:Foundations Español (Coursera)

Offered by Google Cloud,
Serverless Data Processing with Dataflow:Foundations Español (Coursera)

Este curso corresponde a la 1ª parte de una serie de 3 cursos llamada Serverless Data Processing with Dataflow. Para comenzar, en el primer curso haremos un repaso de qué es Apache Beam y cómo se relaciona con Dataflow. Luego, hablaremos sobre la visión de Apache Beam y los beneficios que ofrece su framework de portabilidad. Dicho framework hace posible que un desarrollador pueda usar su lenguaje de programación favorito con su backend de ejecución preferido.

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

Después, le mostraremos cómo Dataflow le permite separar el procesamiento y el almacenamiento y, a la vez, ahorrar dinero. También le explicaremos cómo las herramientas de identidad, acceso y administración interactúan con sus canalizaciones de Dataflow. Por último, veremos cómo implementar el modelo de seguridad adecuado en Dataflow según su caso de uso.

What You Will Learn

  • Demostrar cómo Apache Beam y Cloud Dataflow trabajan juntos para satisfacer las necesidades de procesamiento de datos de su organización
  • Resumir las ventajas del marco de portabilidad de Beam y habilitarlo para sus pipelines de flujo de datos
  • Habilitar Shuffle & Streaming Engine para los pipelines de batch y streaming respectivamente para un máximo rendimiento

Syllabus

WEEK 1
Introducción
Este módulo incluye la descripción del curso y un breve repaso del modelo de programación de Apache Beam y del servicio administrado de Dataflow de Google.
Portabilidad de Beam
En este módulo, estudiaremos cuatro secciones: Portabilidad de Beam, Runner v2, Entornos de contenedores y Transformaciones en varios lenguajes.
Cómo separar el procesamiento y el almacenamiento con Dataflow
En este módulo, aprenderá a separar el procesamiento y el almacenamiento con Dataflow. Además, en él encontrará cuatro secciones: Dataflow, Servicio Dataflow Shuffle, Dataflow Streaming Engine y Programación flexible de recursos.

WEEK 2
IAM, cuotas y permisos
En este módulo, hablaremos sobre los diferentes permisos, cuotas y funciones de IAM que se necesitan para ejecutar Dataflow.
Seguridad
En este módulo, veremos cómo implementar el modelo de seguridad adecuado en Dataflow según su caso de uso.
Resumen
En este curso, haremos un repaso de qué es Apache Beam y cómo se relaciona con Dataflow.

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

Related Courses

Serverless Data Processing with Dataflow: Develop Pipelines (Coursera) Coursera
Google Cloud

Serverless Data Processing with Dataflow: Develop Pipelines (Coursera)

Statistics & Data Analysis Data Science

In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs.

Nov 16th 2026
3 Weeks
SQL Schema Data Processing
Details
Data Science Companion (Coursera) Coursera
MathWorks

Data Science Companion (Coursera)

Statistics & Data Analysis Data Science

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Nov 6th 2026
4 Weeks
MATLAB Machine Learning Regression
Details
Google Cloud Big Data and Machine Learning Fundamentals (edX) EdX
Google Cloud

Google Cloud Big Data and Machine Learning Fundamentals (edX)

Computer Science

Data Analysts, Data Engineers, Data Scientists, and ML Engineers who are getting started with Google Cloud. This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

Self Paced
Self-Paced
Machine Learning Big Data BigQuery
Details
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Statistics & Data Analysis

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced
Excel Data Analysis Microsoft Excel
Details
Basic Data Processing and Visualization (Coursera) Coursera
University of California, San Diego

Basic Data Processing and Visualization (Coursera)

Statistics & Data Analysis Data Science

This is the first course in the four-course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization.

Nov 9th 2026
5-12 Weeks
Python Data Visualization Data Processing
Details
Big Data: el impacto de los datos masivos en la sociedad actual (Coursera) Coursera
Universitat Autònoma de Barcelona

Big Data: el impacto de los datos masivos en la sociedad actual (Coursera)

Statistics & Data Analysis Data Science

La digitalización, la informática e Internet han producido lo que se puede denominar una revolución en la acumulación y utilización de datos. Podemos almacenar y conservar más datos que nunca antes en la historia. Podemos estudiarlos y analizarlos para tomar decisiones y mejorar procesos. Esta nueva capacidad tiene un enorme impacto en todos los ámbitos de la vida social.

Nov 2nd 2026
4 Weeks
Big Data Data Processing Coursera Plus
Details
Parallel Programming in Java (Coursera) Coursera
Rice University

Parallel Programming in Java (Coursera)

CS: Software Engineering CS: Programming

This course teaches learners (industry professionals and students) the fundamental concepts of parallel programming in the context of Java 8. Parallel programming enables developers to use multicore computers to make their applications run faster by using multiple processors at the same time. By the end of this course, you will learn how to use popular parallel Java frameworks (such as ForkJoin, Stream, and Phaser) to write parallel programs for a wide range of multicore platforms including servers, desktops, or mobile devices, while also learning about their theoretical foundations including computation graphs, ideal parallelism, parallel speedup, Amdahl's Law, data races, and determinism.

Nov 9th 2026
4 Weeks
Programming Java Parallel Computing
Details
Data Processing Using Python (Coursera) Coursera
Nanjing University

Data Processing Using Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Nov 23rd 2026
5-12 Weeks
Python Data Structures Data Analysis
Details
Aerial Photography with UAV (Coursera) Coursera
Saint Petersburg State University

Aerial Photography with UAV (Coursera)

CS: Design & Product Computer Science

The purpose of the course is to provide students with knowledge about the technology of aerial photography using unmanned aerial vehicles (UAVs). The course objectives include: knowledge about various aircraft and payloads, the geodetic control creation, flights planning and their implementation, the main stages of data processing and application of the results obtained.

Jul 25th 2022
5-12 Weeks
Photography Computer Science Aircraft
Details
Data Processing with Azure (Coursera) Coursera
LearnQuest

Data Processing with Azure (Coursera)

CS: Information & Technology

This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.

Nov 16th 2026
3 Weeks
Big Data Data Analysis Microsoft Azure
Details