Preparing for the Google Cloud Professional Data Engineer Exam
- Código del Curso GO9071
- Duración 1 Día
- Versión 1.2.2
Otros Métodos de Impartición
Método de Impartición
Este curso está disponible en los siguientes formatos:
-
Clase de calendario
Aprendizaje tradicional en el aula
-
Aprendizaje Virtual
Aprendizaje virtual
Solicitar este curso en un formato de entrega diferente.
Temario
Parte superiorCalendario
Parte superiorDirigido a
Parte superiorThis course is intended for the following participants:
- Cloud professionals interested in taking the Data Engineer certification exam
- Data engineering professionals interested in taking the Data Engineer certification exam
Objetivos del Curso
Parte superior- Position the Professional Data Engineer Certification.
- Provide information, tips, and advice on taking the exam.
- Review each section of the exam, covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate.
- Connect candidates to appropriate target learning.
Contenido
Parte superiorModule 1: Understanding the Professional Data Engineer Certification
- Position the Professional Data Engineer certification among the offerings.
- Distinguish between Associate and Professional.
- Provide guidance between Professional Data Engineer and Associate Cloud Engineer.
- Describe how the exam is administered and the exam rules.
- Provide general advice about taking the exam.
Module 2: Designing Data Processing Systems
- Designing data processing systems.
- Designing flexible data representations.
- Designing data pipelines.
- Designing data processing infrastructure.
Module 3: Building and Operationalizing Data Processing Systems
- Building and operationalizing data structures and databases.
- Building and operationalizing flexible data representations.
- Building and operationalizing pipelines.
- Building and operationalizing processing infrastructure.
Module 4: Operationalizing Machine Learning Models
- Analyzing data and enabling machine learning.
- Deploying an ML pipeline.
- Machine learning terminology review.
- Operationalizing Machine Learning Models: Exam Guide Review.
- Modeling business processes for analysis and optimization.
Module 5: Security, Policy, and Reliability
- Designing for security and compliance.
- Performing quality control.
- Ensuring reliability.
- Visualizing data and advocating policy.
- Ensuring Solution Quality: Exam Guide Review.
Module 6: Resources and Next Steps
- Debrief.
- Preparation Resources.
Pre-requisitos
Parte superiorTo get the most out of this course, participants should: Be familiar with Google Cloud to the level of the Data Engineering on Google Cloud course (suggested, not required)
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- GO9071
- Preparing for the Google Cloud Professional Data Engineer Exam
- Cloud Computing
- GO9071 | Preparing for the Google Cloud Professional Data Engineer Exam | Training Course | Google.