This comprehensive course is designed to support eligible candidates in confidently preparing for the Google Cloud Professional Data Engineer Exam. Whether you are seeking certification or looking to enhance your exam readiness, this course offers valuable insights and guidance to help you succeed.
Throughout the course, you will explore the positioning of the Professional Data Engineer certification, receive exam-related information, tips, and advice, and gain a deep understanding of the exam sections. By focusing on high-level concepts, this course provides a clear roadmap of the skills and areas that candidates need to master to excel in the exam. Additionally, the course equips candidates with optimal study methods to advance their exam preparation effectively.
Featuring comprehensive modules that cover key topics in data processing system design, construction, and operation, as well as the deployment of machine learning models and considerations for security, policies, and reliability, this course ensures candidates are well-prepared for the exam and equipped with essential knowledge for success in the field.
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This course provides comprehensive modules covering data processing system design and construction, machine learning model deployment, and considerations for security and reliability, ensuring candidates are well-prepared for the exam and equipped with essential knowledge for success in the field.
This module introduces the course and its objectives, providing a preview of the topics to be covered.
This module offers insights into the position of the Professional Data Engineer certification, including the latest exam guide information and helpful tips.
Explore the design and construction of data processing systems, focusing on flexible data representation, data pipeline design, and infrastructure considerations.
Learn about the construction and operation of data processing systems, including the use of Cloud Storage, Cloud SQL, and Cloud Bigtable, and gain practical insights through case studies and challenge labs.
Discover the deployment of machine learning models, analyzing and modeling data, and considerations for performance and cost estimation, supported by case studies and practical challenge labs.
Focus on security, policy considerations, and reliability in system design, with a review of solution quality assurance and exam preparation tips.
Conclude the course by exploring additional resources, sample exam questions, and comprehensive review exercises to assess understanding and readiness for the certification exam.
Este curso abrange o processamento de dados sem servidor com Dataflow, incluindo operações, desenvolvimento de pipelines e fundamentos do Apache Beam.
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