Learn with Google : Professional-Data-Engineer日本語 training material for 100% pass
Updated: Jul 29, 2026
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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:
- Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
- Measuring, monitoring, and troubleshooting machine learning models
- Ingesting appropriate data
- Impact of dependencies of machine learning models
- Conversational experiences (e.g., Dialogflow)
- Leveraging pre-built ML models as a service
- Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
- Common sources of error (e.g., assumptions about data)
- Deploying an ML pipeline
- Distributed vs. single machine
- Operationalizing machine learning models
- Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
- Use of edge compute
- ML APIs (e.g., Vision API, Speech API)
- Choosing the appropriate training and serving infrastructure
- Continuous evaluation
- Hardware accelerators (e.g., GPU, TPU)
Who should take the Google Professional Data Engineer exam
Individuals should pursue the exam if they want to demonstrate their expertise and ability to design and develop Data Engineering. Following professional get benefited from Google Professional Data Engineer Certification
- Business analysts
- Data scientists
- Data analysts
- Data engineers
- Developers responsible for managing big data transformation initiatives
- Data architects
Google Professional-Data-Engineer日本語 Exam Overview:
| Certification Vendor: | Google Cloud |
| Exam Name: | Google Cloud Certified Professional Data Engineer Exam |
| Exam Number: | Professional Data Engineer |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | Approximately 50–60 multiple choice and multiple select questions |
| Passing Score: | Not publicly disclosed (scaled scoring system) |
| Available Languages: | English, Japanese, Spanish, Portuguese, French, German |
| Exam Price: | $200 USD |
| Certificate Validity Period: | 2 years |
| Exam Format: | multiple choice, multiple select, case study |
| Related Certifications: | Google Cloud Certified - Associate Cloud Engineer Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Professional Machine Learning Engineer Google Cloud Certified - Professional Data Analytics Engineer |
| Recommended Training: | Google Cloud Data Engineering Learning Path Google Cloud Professional Data Engineer Course (Coursera) |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Data-Engineer日本語 Sample Questions |
| Exam Way: | Online proctored exam or onsite test center (Kryterion Webassessor) |
| Pre Condition: | No formal prerequisites required; recommended experience with data processing and Google Cloud Platform services |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
Prerequisites
There are no formal requirements that the candidates need to meet to qualify for the Google Professional Data Engineer certification. However, without some level of professional experience, it will be difficult for the students to ace the qualifying test. The target individuals are recommended to have three or more years of industry experience, including one or more years of experience in designing and managing solutions with the help of Google Cloud Platform. It is preferable that the applicants also possess some basic database knowledge.
Certification Path
The Google Professional Data Engineer Certification is one of the highest level of certification mainly focussing to the professional Data Engineering.
There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google professional Data Engineer.
You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path
Reference: https://cloud.google.com/certification/data-engineer
Google Professional-Data-Engineer日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 22% | - Data architecture and storage design
|
| Topic 2: Building and operationalizing data processing systems | 24% | - Data processing and transformation
|
| Topic 3: Operationalizing machine learning models | 26% | - ML pipeline integration
|
| Topic 4: Ensuring solution quality | 28% | - Reliability and performance
|
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