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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:

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

Google Professional-Data-Engineer Exam Syllabus Topics:

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

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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.