Preparing for the Google Cloud Professional Data Engineer Exam 日本語版

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/preparing-cloud-professional-data-engineer-exam-jp

Introduction

**Course Review: Preparing for the Google Cloud Professional Data Engineer Exam (日本語版)** In today's digital landscape, the role of data engineers has never been more critical. Those looking to solidify their expertise in the field may find the course "Preparing for the Google Cloud Professional Data Engineer Exam 日本語版" on Coursera to be an invaluable resource. This course is designed not only for candidates who are eligible to take the certification exam but also for those who wish to strengthen their foundational knowledge in preparation for future certification. ### Course Overview This course offers essential information to help candidates confidently approach the Google Cloud Professional Data Engineer Exam. It's particularly beneficial for those who may not have met the exam prerequisites yet, serving as a comprehensive introduction to what is required for success. ### Syllabus Breakdown The curriculum is meticulously crafted to guide learners through the essential themes of the exam: 1. **Introduction** - Sets the stage for the course, outlining objectives and desired outcomes. 2. **Understanding the Professional Data Engineer Certification** - This module covers fundamental knowledge regarding the certification exam, including the examination process and common misconceptions about its nature. It helps demystify the certification landscape and prepares learners with valuable insights. 3. **Designing Data Processing Systems** - Learners will gain skills in designing potential data processing systems that could be tested in the exam, focusing on data structures and databases. The tips and examples provided are practical, allowing for real-world application of the concepts. 4. **Building and Operating Data Processing Systems** - This section emphasizes assembling data processing from various components, including comprehensive service utilization. It equips learners with the knowledge to build practical data systems that are robust and reliable. 5. **Operating Machine Learning Models** - The exam covers data analysis, business process optimization, and machine learning. This module provides learners with necessary skills through tips and examples relevant to the exam's themes. 6. **Security, Policies, and Reliability** - Understanding security measures, policies, and compliance is essential for data engineers. This module prepares learners for potential exam questions while reinforcing the importance of reliability within data systems. 7. **Resources and Next Steps** - Finally, the course concludes with an overview of resources available for further study of specific themes that may appear on the exam. This encourages continuous learning beyond the course. ### Recommendation I highly recommend the "Preparing for the Google Cloud Professional Data Engineer Exam 日本語版" course for anyone serious about advancing their career in data engineering. The course does not only prepare you for the exam itself but also provides a solid foundation of knowledge that can be applied in the workplace. Even if you're not yet eligible to take the certification exam, this course serves as an excellent stepping stone—equipping you with the skills and knowledge necessary to navigate the complexities of data engineering. ### Conclusion In summary, this course on Coursera stands out due to its structured approach and comprehensive coverage of the syllabus. With its practical tips, real-world examples, and a focus on building essential skills, it is an essential resource for anyone preparing for the Google Cloud Professional Data Engineer Exam. Whether you're a newcomer to the field or looking to refresh your knowledge, this course is well worth the investment of your time and effort.

Syllabus

本コースについて

はじめに

Professional Data Engineer 認定資格について

認定資格試験に関する基本的な知識を習得し、試験のプロセスや性質に関する混同や誤解を取り除きます。

データ処理システムの設計

試験で出題される可能性があるデータ処理システムの設計スキル、データ構造のスキル、データベースのスキルに関するヒントと例。

データ処理システムの構築と運用化

各部分からのデータ処理の組み立てと、フルサービスの利用を含む、データ処理システムの構築に関するヒントと例。

機械学習モデルの運用化

試験で出題される可能性があるデータ分析、ビジネス プロセスの分析と最適化、機械学習の各スキルに関するヒントと例。

セキュリティ、ポリシー、信頼性

試験で出題される可能性がある信頼性、ポリシー、セキュリティ、コンプライアンスの各スキルに関するヒントと例。

リソースと次のステップ

試験で出題される可能性がある特定のテーマの詳細を学習するためのリソースの確認