This program provides the skills you need to advance your career in data engineering and provides a pathway to earn the industry-recognized Google Cloud Professional Data Engineer certification. Through a combination of presentations, demos, and labs, you'll enable data-driven decision making by collecting, transforming, and publishing data; and you'll gain real world experience through a number of hands-on Qwiklabs projects that you can share with potential employers. You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models. For learners looking to get certified, this program will also provide sample questions similar to those on the exam, including solutions and practice exam quizzes that simulate the exam-taking experience. Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers. If you'd like to earn your Google Cloud certification, you will need to register for and pass the certification exam. Please note that this program helps equip you with the skills you need to take the certification exam, but the certification and certification fee is not included in the cost of this training program.
Certificado profesional de Data Engineering with GCP
Advance your career in data engineering.
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Qué aprenderás
Learn the skills needed to be successful in a data engineer role
Prepare for the Professional Data Engineer certification
Learn about the infrastructure and platform services provided by Google Cloud Platform
¿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 Platform Big Data and Machine Learning Fundamentals
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • Google services are currently unavailable in China.
Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs. In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis. Pre-requisites • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Python
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China.
Serverless Machine Learning with Tensorflow on Google Cloud Platform
This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China.
Acerca de Google Cloud
Preguntas Frecuentes
¿Cuál es la política de reembolsos?
¿Puedo inscribirme en un solo curso?
¡Sí! Para empezar, haz clic en la tarjeta del curso que te interesa e inscríbete. Puedes inscribirte y completar el curso para obtener un certificado que puedes compartir o puedes acceder al curso como oyente para ver los materiales del curso de manera gratuita. Cuando te suscribes a un curso que forma parte de un Certificado, te suscribes automáticamente a todo el Certificado. Visita el panel del estudiante para realizar un seguimiento de tu progreso.
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
Este curso es completamente en línea, de modo que no necesitas ir a un aula en persona. Puedes acceder a tus lecciones, lecturas y tareas en cualquier momento y cualquier lugar a través de Internet o tu dispositivo móvil.
How long does it take to complete the Professional Certificate?
This Professional Certificate is designed to be completed in one and a half months at 5 hours per week.
What background knowledge is necessary?
To get the most out of this program, learners should have basic proficiency with a common query language such as SQL; experience developing applications using a common programming language such as Python; experience with data modeling, extract, transform, load activities ; and familiarity with machine learning and/or statistics.
Do I need to take the courses in a specific order?
We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Qwiklabs projects, as these hands-on labs build upon the work you complete in preceding courses.
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