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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:
- Deploying an ML pipeline
- ML APIs (e.g., Vision API, Speech API)
- Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
- Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
- Measuring, monitoring, and troubleshooting machine learning models
- Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
- Use of edge compute
- Impact of dependencies of machine learning models
- Distributed vs. single machine
- Ingesting appropriate data
- Leveraging pre-built ML models as a service
- Continuous evaluation
- Choosing the appropriate training and serving infrastructure
- Hardware accelerators (e.g., GPU, TPU)
- Operationalizing machine learning models
- Conversational experiences (e.g., Dialogflow)
- Common sources of error (e.g., assumptions about data)
Exam Details
The Google Professional Data Engineer certification exam has the duration of 2 hours. The qualifying test is made up of multiple-select and multiple-choice questions. The exam is available either in Japanese or English. To register for it, you are required to go through the official webpage and pay the fee of $200 plus applicable taxes. While completing the registration process, the potential individuals can choose the preferred method of exam delivery. It can be taken in person at the nearest testing center or online from a remote location.
Reference: https://cloud.google.com/certification/data-engineer
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Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Preparing and using data for analysis (~15% of the exam) | 15% | - Sharing data securely
|
| Storing the data (~20% of the exam) | 20% | - Using a data lake
|
| Ingesting and processing the data (~20% of the exam) | 20% | - Deploying and operationalizing the pipelines
|
| Designing data processing systems (~30% of the exam) | 30% | - Designing data processing resources
|
| Maintaining and automating data workloads (~15% of the exam) | 15% | - Automating data processes
|
Google Certified Professional Data Engineer Sample Questions:
Which of the following statements about the Wide & Deep Learning model are true? (Select 2 answers.)
- A. A good use for the wide and deep model is a recommender system.
- B. The wide model is used for generalization, while the deep model is used for memorization.
- C. A good use for the wide and deep model is a small-scale linear regression problem.
- D. The wide model is used for memorization, while the deep model is used for generalization.
Correct Answer: A,D 🗳️
Explanation: Only visible for RealValidExam members. You can sign-up / login (it's free).
You are designing a messaging system by using Pub/Sub to process clickstream data with an event-driven consumer app that relies on a push subscription. You need to configure the messaging system that is reliable enough to handle temporary downtime of the consumer app.
You also need the messaging system to store the input messages that cannot be consumed by the subscriber. The system needs to retry failed messages gradually, avoiding overloading the consumer app, and store the failed messages after a maximum of 10 retries in a topic. How should you configure the Pub/Sub subscription?
- A. Increase the acknowledgement deadline to 10 minutes.
- B. Use exponential backoff as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
- C. Use exponential backoff as the subscription retry policy, and configure dead lettering to the same source topic with maximum delivery attempts set to 10.
- D. Use immediate redelivery as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
Correct Answer: B 🗳️
You need to connect multiple applications with dynamic public IP addresses to a Cloud SQL instance. You configured users with strong passwords and enforced the SSL connection to your Cloud SQL instance. You want to use Cloud SQL public IP and ensure that you have secured connections. What should you do?
- A. Leave the Authorized Network empty. Use Cloud SQL Auth proxy on all applications.
- B. Add CIDR 0.0.0.0/0 network to Authorized Network. Use Identity and Access Management (IAM) to add users.
- C. Add all application networks to Authorized Network and regularly update them.
- D. Add CIDR 0.0.0.0/0 network to Authorized Network. Use Cloud SQL Auth proxy on all applications.
Correct Answer: A 🗳️
You are deploying 10,000 new Internet of Things devices to collect temperature data in your warehouses globally. You need to process, store and analyze these very large datasets in real time. What should you do?
- A. Send the data to Google Cloud Datastore and then export to BigQuery.
- B. Export logs in batch to Google Cloud Storage and then spin up a Google Cloud SQL instance, import the data from Cloud Storage, and run an analysis as needed.
- C. Send the data to Google Cloud Pub/Sub, stream Cloud Pub/Sub to Google Cloud Dataflow, and store the data in Google BigQuery.
- D. Send the data to Cloud Storage and then spin up an Apache Hadoop cluster as needed in Google Cloud Dataproc whenever analysis is required.
Correct Answer: C 🗳️
Explanation: Only visible for RealValidExam members. You can sign-up / login (it's free).
You have a requirement to insert minute-resolution data from 50,000 sensors into a BigQuery table. You expect significant growth in data volume and need the data to be available within 1 minute of ingestion for real-time analysis of aggregated trends. What should you do?
- A. Use the MERGE statement to apply updates in batch every 60 seconds.
- B. Use a Cloud Dataflow pipeline to stream data into the BigQuery table.
- C. Use bq load to load a batch of sensor data every 60 seconds.
- D. Use the INSERT statement to insert a batch of data every 60 seconds.
Correct Answer: B 🗳️
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