Preparing for the Google Cloud Professional Data Engineer Exam en Español from Coursera

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.

What's inside

Syllabus

Bienvenido a Preparing for the Professional Data Engineer Exam

Descripción de este módulo.

Diseño de sistemas de procesamiento de datos

Traffic lights

Read about what's good

what should give you pause

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

Reviews summary

Preparación para el examen ingeniero de datos gcp

Según los estudiantes, este curso de Google Cloud está bien estructurado, siguiendo de cerca el esquema de la guía oficial del examen de Professional Data Engineer. Muchos consideran que es un excelente punto de partida o un buen repaso de los conceptos clave. Sin embargo, varios comentarios sugieren que la profundidad en ciertos temas puede ser limitada y que se requiere estudio adicional, incluyendo la documentación oficial de GCP y experiencia práctica, para estar completamente preparado. Los laboratorios y preguntas de práctica son vistos generalmente como útiles. El hecho de estar íntegramente en español es un punto muy valorado por los hablantes nativos.

Los labs y ejercicios son útiles.

"Los laboratorios de desafío son muy buenos para poner a prueba tus conocimientos."

"Las preguntas de práctica al final del curso son bastante representativas del examen real."

"Me parecieron muy útiles los ejercicios prácticos para entender mejor los servicios."

Curso totalmente en español.

"Agradezco mucho que todo el contenido, incluyendo los videos, esté en español nativo."

"Es excelente tener un recurso de preparación para el examen tan completo en mi idioma."

"La calidad de la traducción y la locución en español es muy buena."

La estructura sigue la guía oficial del examen.

"El curso sigue muy bien la estructura del examen de Professional Data Engineer."

"Me gusta cómo está organizado según el temario oficial de Google."

"La forma en que presenta los temas se alinea perfectamente con lo que espera el examen."

Algunos temas no se cubren con suficiente detalle.

"Siento que algunos servicios importantes para el examen se explican de forma muy superficial."

"La explicación de ciertos conceptos avanzados podría ser más detallada."

"Para ciertas secciones, tuve que buscar explicaciones más profundas en la documentación oficial."

Requiere estudio y experiencia adicional.

"Este curso es solo un punto de partida, necesitarás complementar con documentación oficial y práctica."

"No creo que sea suficiente por sí solo para pasar el examen sin experiencia previa considerable."

"Es un buen repaso, pero para profundizar hay que buscar otros recursos y hacer muchos más labs."

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

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Organize your notes, assignments, and resources to enhance your understanding of course materials.

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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

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Refresh your understanding of foundational data engineering concepts to prepare for the course.

Browse courses on Data Engineering

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Review textbooks or online resources
Complete practice exercises or quizzes
Discuss concepts with peers or mentors

Revise the fundamentals of data processing

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Revisiting the fundamentals will strengthen your foundational skills and make the course content easier to grasp.

Browse courses on Data Processing

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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

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Find a mentor in the field of data engineering

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Gain guidance and support from an experienced data engineer to enhance your learning.

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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

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Expand your professional network and gain insights from experienced data engineers.

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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

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Begin building and refining your foundational skills for designing and implementing data pipelines.

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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

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Working with real-world data provides practical experience and helps you connect theoretical concepts with practical applications.

Browse courses on Data Analysis

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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

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Gain hands-on experience and learn about cutting-edge data engineering techniques.

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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

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Practice your ability to analyze real-world data engineering challenges.

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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

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Creating content helps you synthesize and retain information, while also contributing to the broader data engineering community.

Browse courses on Technical Writing

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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

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Gain practical experience and contribute to the data engineering community by working on an open-source project.

Browse courses on Open Source

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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

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Demonstrate your understanding of data engineering best practices by creating a comprehensive technical document.

Browse courses on Technical Writing

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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.

See salaries and explore the career path for Data Engineer

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.

See salaries and explore the career path for Machine Learning Engineer

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.

See salaries and explore the career path for Data Scientist

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.

See salaries and explore the career path for Data Architect

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.

See salaries and explore the career path for Business Analyst

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Statistician

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.

See salaries and explore the career path for Data Analyst

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.

See salaries and explore the career path for Database Administrator

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.

See salaries and explore the career path for Quantitative Analyst

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.

See salaries and explore the career path for Actuary

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.

See salaries and explore the career path for Financial Analyst

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.

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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.

See salaries and explore the career path for Operations Research Analyst

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.

See salaries and explore the career path for Policy Analyst