Difficulty in Attempting Google Professional Data Engineer Exam Certification

If the user has successfully passed the professional-data-engineer practice exam and has been through professional-data-engineer exam dumps then the certification exam will not be too much difficult as the user has shown aptitude for understanding complicated processes.

Reference: https://cloud.google.com/certification/data-engineer

Target Audience

The candidates for this certification are the data engineers or those aiming to become one. These individuals should have the capacity to allow data-driven decision-making through the collection, transformation, and publishing of data. They have the expertise in designing, building, and operationalizing secure data processing systems and monitoring the same. This is with the specific emphasis on compliance and security, fidelity and reliability, portability and flexibility, as well as efficiency and scalability.

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Understanding functional and technical aspects of Google Professional Data Engineer Exam Operationalizing machine learning models

The following will be discussed here:

• Hardware accelerators (e.g., GPU, TPU)
• Ingesting appropriate data
• Operationalizing machine learning models
• Continuous evaluation
• Distributed vs. single machine
• ML APIs (e.g., Vision API, Speech API)
• Common sources of error (e.g., assumptions about data)
• Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
• Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
• Use of edge compute
• Measuring, monitoring, and troubleshooting machine learning models
• Impact of dependencies of machine learning models
• Conversational experiences (e.g., Dialogflow)
• Choosing the appropriate training and serving infrastructure
• Deploying an ML pipeline
• Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
• Leveraging pre-built ML models as a service

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Preparation Process

To perform well in the Google Professional Data Engineer certification exam, the candidates must be ready to devote ample time to preparation. There is a host of study materials available on the Internet, but if you want to be confident in the authenticity of the resources that you use, it is best to refer to the official platform. Google recommends that the applicants follow the Professional Data Engineer learning path, which is a comprehensive option involving in-person classes, online training, hands-on labs, and other resources from Google Cloud.

Besides that, it is recommended that the students use the official sample questions to familiarize themselves with the question formats that they will encounter during the actual exam. The official webpage also contains additional resources such as Google Cloud documentation and Google Cloud solutions. There is also an option of joining the subject-related webinar to get valuable preparation tips from the Google experts.

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