- Information Engineering
- Google Cloud
- Bigquery
- Tensorflow
- Cloud Computing
- Google Cloud Platform
Certificado profesional de Prepárate para una certificación en Google Cloud: ingeniero de datos de la nube
Advance your career in data engineering
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Qué aprenderás
Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.
Employ BigQuery to carry out interactive data analysis.
Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
Choose between different data processing products on Google Cloud.
Habilidades que obtendrás
Acerca de este Certificado profesional
Proyecto de aprendizaje aplicado
This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.
These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
¿Qué es un certificado profesional?
Desarrolla las habilidades necesarias para completar el trabajo
Ya sea que desees comenzar una nueva carrera o cambiar tu carrera actual, los certificados profesionales de Coursera te ayudan a prepararte para el puesto. Aprende a tu propio ritmo, en el momento y el lugar que te resulten más cómodos. Inscríbete hoy mismo y descubre una nueva carrera con una prueba gratuita de 7 días. Puedes pausar tus clases o finalizar la suscripción en cualquier momento.
Proyectos prácticos
Aplica tus habilidades en proyectos prácticos y desarrolla una cartera que demuestre tu preparación para los trabajos a los posibles empleadores. Deberás terminar los proyectos correctamente para obtener tu certificado.
Obtén una credencial profesional
Cuando completas todos los cursos del programa, obtienes un certificado que puedes compartir con tu red profesional, así como acceso a los recursos de apoyo profesional que te ayudarán a comenzar tu nueva carrera. Muchos certificados profesionales tienen socios interesados en contratar personal que reconocen la credencial del certificado profesional, y otros pueden ayudarte en tu preparación para el examen de un certificado. Puedes ver más información en las páginas del certificado profesional particular en donde aplica.

Hay 6 cursos en este Certificado profesional
Google Cloud Big Data and Machine Learning Fundamentals
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.
Modernizing Data Lakes and Data Warehouses with Google Cloud
The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
Building Batch Data Pipelines on Google Cloud
Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
Building Resilient Streaming Analytics Systems on Google Cloud
Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.
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Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Preguntas Frecuentes
¿Cuál es la política de reembolsos?
¿Puedo inscribirme en un solo curso?
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
How long does it take to complete the Professional Certificate?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
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