From the course: "The best way to prepare for the exam is to be competent in the skills required of the job." This course uses a top-down approach to recognize knowledge and skills already known, and to surface information and skill areas for additional preparation. You can use this course to help create your own custom preparation plan. It helps you distinguish what you know from what you don't know. And it helps you develop and practice skills required of practitioners who perform this job.
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The course follows the organization of the Exam Guide outline, presenting highest-level concepts, "touchstones", for you to determine whether you feel confident about your knowledge of that area and its dependent concepts, or if you want more study. You also will learn about and have the opportunity to practice key job skills, including cognitive skills such as case analysis, identifying technical watchpoints, and developing proposed solutions. These are job skills that are also exam skills. You will also test your basic abilities with Activity Tracking Challenge Labs. And you will have many sample questions similar to those on the exam, including solutions. The end of the course contains an ungraded practice exam quiz, followed by a graded practice exam quiz that simulates the exam-taking experience.
What You Will Learn
- Review each section of the exam using highest-level concepts to identify what is already known and surface gap areas for study.
- Practice case study analysis and solution proposal methods and thinking skills.
- Learn information, tips, and general advice about how to prepare for the exam.
- Integrate prior technical skills into practical skills for the job role. Help you become a Data Engineer.
Course 6 of 6 the Data Engineering with Google Cloud Professional Certificate program.
Syllabus
WEEK 1
Understanding the Professional Data Engineer Certification
Establish basic knowledge about the certification exam and eliminate any confusion or misunderstandings about the process and nature of the exam itself.
WEEK 2
Designing Data Processing Systems
Tips and examples covering data processing systems design skills, data structures, and database skills that could be tested on the exam.
WEEK 3
Building and Operationalizing Data Processing Systems
Tips and examples covering the building of data processing systems, including assembling data processing from parts, as well as using full services.
WEEK 4
Operationalizing Machine Learning Models
Tips and examples covering data analysis, analysis and optimization of business processes, and machine learning skills that could be tested on the exam.
WEEK 5
Security, Policy, and Reliability
Tips and examples covering reliability, policies, security, and compliance skills that could be tested on the exam.
WEEK 6
Resources and next steps
Resources for learning more about identified subjects that could be tested on the exam.
