We may earn an affiliate commission when you visit our partners.
Course image
Google Cloud Training

Del curso: "La mejor manera de prepararse para el examen es ser competente en las habilidades necesarias para el trabajo".

En este curso, se emplea un enfoque descendente a fin de identificar las habilidades y los conocimientos adquiridos, así como poner en evidencia la información y las áreas de habilidades que requieren una preparación adicional. Puede aprovechar este curso para crear su propio plan de preparación personalizado. Lo ayudará a distinguir lo que sabe de lo que no. Además, le permitirá desarrollar y practicar las habilidades que se les exigen a los profesionales que realizan este trabajo.

Read more

Del curso: "La mejor manera de prepararse para el examen es ser competente en las habilidades necesarias para el trabajo".

En este curso, se emplea un enfoque descendente a fin de identificar las habilidades y los conocimientos adquiridos, así como poner en evidencia la información y las áreas de habilidades que requieren una preparación adicional. Puede aprovechar este curso para crear su propio plan de preparación personalizado. Lo ayudará a distinguir lo que sabe de lo que no. Además, le permitirá desarrollar y practicar las habilidades que se les exigen a los profesionales que realizan este trabajo.

El curso está organizado según el esquema de la Guía para el examen. Se le presentan los conceptos de mayor nivel (es decir, los conceptos clave) para que determine si se siente seguro con respecto a sus conocimientos sobre esa área y los conceptos relacionados, o si necesita estudiar más. También podrá aprender y practicar las habilidades clave para el trabajo, incluidas las cognitivas, como el análisis de casos, la identificación de puntos de análisis técnicos y el desarrollo de las soluciones propuestas. Esas habilidades para el trabajo también son necesarias a fin de rendir el examen. Por otra parte, pondrá a prueba sus capacidades básicas con los Labs de desafío de seguimiento de actividades. Además, tendrá muchas preguntas de ejemplo similares a las del examen, incluidas las soluciones. Al final del curso, se incluyen dos tests del examen de práctica: uno sin calificación seguido de otro con calificación, que simula la experiencia de rendir el examen.

Enroll now

What's inside

Syllabus

Bienvenido a Preparing for the Professional Data Engineer Exam
Descripción de este módulo.
Diseño de sistemas de procesamiento de datos
Read more
Compilación y puesta en funcionamiento de sistemas de procesamiento de datos
Puesta en funcionamiento de modelos de aprendizaje automático
Confiabilidad, políticas y seguridad para garantizar una solución de calidad
Recursos y próximos pasos

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Destinado para profesionales de la industria que desean prepararse para el examen Professional Data Engineer de Google Cloud
Ofrece una descripción general de las habilidades y conocimientos requeridos para rendir exitosamente el examen
Proporciona laboratorios prácticos para desarrollar y practicar las habilidades necesarias para el examen
Incluye preguntas de ejemplo similares a las del examen para reforzar el aprendizaje
Dos simulacros de examen para ayudar a los estudiantes a familiarizarse con el formato y los requisitos del examen
Requiere conocimientos y experiencia previos en diseño e implementación de sistemas de procesamiento de datos

Save this course

Save Preparing for the Google Cloud Professional Data Engineer Exam en Español to your list so you can find it easily later:
Save

Reviews summary

Thorough preparation for data engineer exam

This course is a comprehensive resource for preparing for the Google Cloud Professional Data Engineer Exam. It covers all the necessary skills and knowledge, and provides many practice questions and labs. Students who have taken the course have found it to be very helpful in their preparation.

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 Preparing for the Google Cloud Professional Data Engineer Exam en Español with these activities:
Compile and organize your course materials
Organize your notes, assignments, and resources to enhance your understanding of course materials.
Show steps
  • Gather and organize your course materials
  • Create a system for organizing and referencing materials
  • Review and update your materials regularly
Review fundamental concepts in data engineering
Refresh your understanding of foundational data engineering concepts to prepare for the course.
Browse courses on Data Engineering
Show steps
  • Review textbooks or online resources
  • Complete practice exercises or quizzes
  • Discuss concepts with peers or mentors
Revise the fundamentals of data processing
Revisiting the fundamentals will strengthen your foundational skills and make the course content easier to grasp.
Browse courses on Data Processing
Show steps
  • Review lecture notes and slides from previous data processing courses
  • Solve practice problems and exercises to test your understanding
  • Complete online quizzes or assessments to gauge your knowledge level
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Find a mentor in the field of data engineering
Gain guidance and support from an experienced data engineer to enhance your learning.
Browse courses on Mentorship
Show steps
  • Identify potential mentors in your network or through industry events
  • Reach out to potential mentors and express your interest
  • Set up regular meetings or communication channels
Network with professionals in the field of data engineering
Expand your professional network and gain insights from experienced data engineers.
Browse courses on Networking
Show steps
  • Attend industry events and meetups
  • Join online communities and forums
  • Reach out to professionals for informational interviews
Build a data pipeline with an end-to-end architecture
Begin building and refining your foundational skills for designing and implementing data pipelines.
Show steps
  • Establish your project's scope and objectives
  • Design the pipeline architecture
  • Select and integrate the necessary tools and technologies
  • Implement the pipeline and test its functionality
Analyze real-world data examples
Working with real-world data provides practical experience and helps you connect theoretical concepts with practical applications.
Browse courses on Data Analysis
Show steps
  • Obtain datasets from reputable sources
  • Explore and familiarize yourself with the data
  • Apply data processing techniques to clean, transform, and analyze the data
  • Interpret the results and draw meaningful conclusions
Attend a workshop on advanced data engineering techniques
Gain hands-on experience and learn about cutting-edge data engineering techniques.
Show steps
  • Research and identify relevant workshops
  • Register and attend the workshop
  • Actively participate in the workshop
  • Follow up with the workshop organizers or attendees
Solve case studies related to data engineering
Practice your ability to analyze real-world data engineering challenges.
Browse courses on Case Studies
Show steps
  • Review case studies and identify key issues
  • Develop and evaluate potential solutions
  • Discuss your findings with peers or mentors
Write a blog post or article on a data engineering topic
Creating content helps you synthesize and retain information, while also contributing to the broader data engineering community.
Browse courses on Technical Writing
Show steps
  • Choose a specific data engineering topic to write about
  • Research and gather relevant information
  • Organize and outline your thoughts
  • Write the blog post or article, ensuring clarity, accuracy, and conciseness
  • Publish your content on a reputable platform
Contribute to an open-source data engineering project
Gain practical experience and contribute to the data engineering community by working on an open-source project.
Browse courses on Open Source
Show steps
  • Identify suitable open-source projects
  • Join the project community and introduce your contributions
  • Work on specific tasks or features
  • Collaborate with other contributors and seek feedback
Create a technical document on data engineering best practices
Demonstrate your understanding of data engineering best practices by creating a comprehensive technical document.
Browse courses on Technical Writing
Show steps
  • Research and gather information on data engineering best practices
  • Organize and structure the document
  • Write clear and concise content
  • Proofread and edit the document
  • Share the document with others for feedback

Career center

Learners who complete Preparing for the Google Cloud Professional Data Engineer Exam en Español will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers connect data sources such as databases, servers, or data lakes, to transform, organize, and manage data assets. They then use the transformed data to create useful analytics and information for end users, business intelligence teams, data analysts, and data scientists. This course will be particularly useful in teaching you how to design and compile data processing systems.
Data Architect
Data Architects design, build, and maintain the architecture of data systems. They work with stakeholders to understand business needs, and then design and implement data solutions that meet those needs. This course will help you learn how to design data processing systems, which is a key skill for Data Architects.
Machine Learning Engineer
Machine Learning Engineers design, build, deploy, and maintain machine learning models. They typically have a background in computer science, statistics, or a related field, as well as experience with programming languages and frameworks like Python, R, or Java. This course will help you learn how to operationalize machine learning models, which is a key skill for Machine Learning Engineers.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course will be useful in teaching you how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Data Scientists.
Business Analyst
Business Analysts analyze business processes and systems to identify areas for improvement. They then design and implement solutions to improve efficiency and effectiveness. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Business Analysts.
Database Administrator
Database Administrators design, implement, and maintain database systems. They work with stakeholders to understand business needs, and then design and implement database solutions that meet those needs. This course will help you learn how to compile and operationalize data processing systems, which is a key skill for Database Administrators.
Financial Analyst
Financial Analysts use financial data to make recommendations for investment decisions. They work with clients to understand their financial goals, and then develop and implement investment strategies that meet those goals. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Financial Analysts.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of fields, including finance, risk management, and healthcare. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Quantitative Analysts.
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of fields, including insurance, finance, and healthcare. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Actuaries.
Policy Analyst
Policy Analysts develop and evaluate public policies. They work with stakeholders to understand the problem, and then develop and implement policies that address the problem. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Policy Analysts.
Market Researcher
Market Researchers collect and analyze data about consumer behavior. They use this data to help businesses understand their customers and make informed decisions about product development and marketing campaigns. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Market Researchers.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They work in a variety of fields, including manufacturing, healthcare, and logistics. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Operations Research Analysts.
Statistician
Statisticians collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, finance, and marketing. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Statisticians.
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with stakeholders to understand business needs, and then design and implement software solutions that meet those needs. This course will help you learn how to compile and operationalize data processing systems, which is a key skill for Software Engineers.
Data Analyst
Data Analysts use data to solve business problems. They collect, clean, and analyze data, and then use the results of their analysis to make recommendations for business decisions. This course will help you learn how to analyze cases, identify technical analysis points, and develop proposed solutions, all of which are key skills for Data Analysts.

Reading list

We've selected ten 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 Preparing for the Google Cloud Professional Data Engineer Exam en Español.
Este libro proporciona una base sólida para comprender los desafíos de diseñar y construir sistemas de procesamiento de datos a gran escala. Cubre temas esenciales como el almacenamiento de datos distribuidos, el procesamiento de flujos y la gestión de metadatos.
Este libro proporciona una visión general de los conceptos y prácticas fundamentales de gestión de datos. Cubre temas como el modelado de datos, el diseño de bases de datos y la administración de datos, que sientan una base sólida para la ingeniería de datos.
Este libro proporciona una base sólida en estadística y minería de datos, que son fundamentales para el análisis y la interpretación de datos. Cubre temas como el muestreo, la inferencia estadística y los algoritmos de minería de datos.
Este libro se centra en el uso de la biblioteca fastai y PyTorch para el aprendizaje profundo. Proporciona una introducción práctica al aprendizaje profundo y cubre temas como la creación de modelos, el entrenamiento y la implementación.
Este libro explora las tecnologías y prácticas nativas de la nube para la gestión de datos. Cubre temas como la gestión de bases de datos, el análisis de datos y la integración de datos, en el contexto de la computación en la nube.
Este libro ofrece una introducción práctica a la ciencia de datos. Cubre temas como la limpieza de datos, el modelado y la visualización, y es valioso para principiantes que buscan comprender los fundamentos de la ciencia de datos.
Este libro proporciona una visión general del panorama del aprendizaje automático. Cubre temas como los diferentes algoritmos de aprendizaje automático, sus fortalezas y debilidades, y es valioso para comprender las últimas tendencias y desarrollos en el aprendizaje automático.
Este libro ofrece una introducción práctica al aprendizaje automático con Python y scikit-learn. Cubre temas como la preparación de datos, el entrenamiento de modelos y la evaluación, y es valioso para principiantes que buscan adquirir habilidades prácticas en el aprendizaje automático.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Preparing for the Google Cloud Professional Data Engineer Exam en Español.
Preparing for the Google Cloud Professional Cloud...
Most relevant
Gestión del alcance: el qué de la triple restricción
Most relevant
Curso online preparación del título oficial inglés B1 o B2
Most relevant
Examen CSCM - ISCEA Certified Supply Chain Manager - en...
Most relevant
Trabajo en equipo en el ámbito jurídico
Most relevant
Negociación exitosa: Estrategias y habilidades esenciales...
Most relevant
Negociación exitosa: Estrategias y habilidades esenciales...
Most relevant
Aspectos básicos del diseño de la experiencia del usuario
Most relevant
Habilidades de Excel para el negocio: Intermedio I
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser