This course uses a top-down approach to recognize knowledge and skills already known, and to surface information and skill areas for additional preparation. Students can use this course to help create their own custom preparation plan. It helps distinguish what they know from what they don't know. And it helps students develop and practice skills required of practitioners who perform this job. The course follows the organization of the Exam Guide outline, presenting highest-level concepts, 'touchstones', for students to determine whether they feel confident about their knowledge of that area and its dependent concepts, or if they want more study. They 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. They will also test their basic abilities with Activity Tracking Challenge Labs. And they 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.
Cloud professionals who intend to take the Professional Data Engineer certification exam Knowledge and experience with GCP, equivalent to GCP Big Data and Machine Learning Fundamentals course Knowledge of data engineering and ML solutions, equivalent to Data Engineering on GCP course Industry experience with data engineering and cloud computing .
- Familiarity with Google Cloud Platform to the level of the Data Engineering on Google Cloud Platform course (suggested, not required)
Understanding the Professional Data Engineer Certificationul> Establish basic knowledge about the certification exam and eliminate any confusion or misunderstandings about the process and nature of the exam itself./li>Sample Case Studies for the Professional Data Engineer Examul> In-depth review of the Case Studies provided for exam preparation/li>Designing and Building (Review and preparation tips)ul> Tips and examples covering data processing systems design skills, data structures, and database skills that could be tested on the exam./li>Analyzing and Modeling (Review and preparation tips)ul> Tips and examples covering data analysis, analysis and optimization of business processes, and machine learning skills that could be tested on the exam./li>Reliability, Policy, and Security (Review and preparation tips)ul> Tips and examples covering reliability, policies, security, and compliance skills that could be tested on the exam./li>Resources and next stepsul> Resources for learning more about identified subjects that could be tested on the exam./li>